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1
Lozhkin, Leonid D., and Alexander A. Kuzmenko. "Investigation of CIE color spaces for differences in color differentiation thresholds in different regions of the color locus." Physics of Wave Processes and Radio Systems 24, no. 3 (2021): 107–10. http://dx.doi.org/10.18469/1810-3189.2021.24.3.107-110.
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The equidistance of the color space plays a significant role in determining the color difference in color transmission systems. Strictly equal contrasting color spaces can be considered only those color spaces in which equal changes in the visual perception of color are provided with an equal change in the color coordinates in this color space. Currently, the International Commission on Lighting (CIE) has adopted a number of color spaces called equal-contrast. The article presents the results of the study of color spaces adopted by CIE for equal contrast, i.e. on the differences in the thresholds of color differentiation in different areas of the color locus. The article investigated such color spaces as CIE 1931 (RGB), CIE 1931 (x, y), CIE 1960 (u, v), CIE 1976 (u*, v*), CIE LAB (a*, b*).
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Tong, Li Ping, Bin Peng, and Yi Wei Fei. "The Color Recognition of Jet Fuel Silver Corrosion Images Based on Color Difference Formula." Advanced Materials Research 503-504 (April 2012): 1033–36. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1033.
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This article introduces the basic theoretical knowledge of the multi-color space and its color difference formula. By research and experiment, it validates that HSV and CIE L * a * b * color space and its corresponding color difference formula, which are used in the color recognition of jet fuel silver corrosion image, and their results are mostly in accordance with the recognition results by the naked eyes. And it also proves the feasibility of these two methods for the color recognition of jet fuel silver corrosion. Silver strip corrosion experiment must be tested as one of jet fuel corrosion detection items in jet fuel accepting, providing and storage process. The examination, whether jet fuel is qualified or not, is mainly due to silver corrosion’s color judgment. For computer visual system, the color is the character of object surface, and it is mankind recognition system to the object surface, light shine and visual condition’s comprehensive effect, and it has important function in the picture’s partition and identifying field. The color that is put up by visible light is continuous, and in order to measure and calculate conveniently, some scholars successively establish more than ten color spaces, which are mainly divided three types, by the HSV color space with RGB, HIS, and Munsell color spaces etc. According to particular application color space, YUV and YIQ and CMY color space are adopted by the television system, and CIE color space then includes CIE, XYZ, Lab and Luv etc. This article comparatively studies representative color space as well as RGB, HIS, CMY, YUV and CIE Lab color spaces, which are used for jet fuel silver strip corrosion image’s color recognition accuracy, and this article finally ensures a kind of color space and color difference formula which are applied to jet fuel silver strip corrosion image’s color recognition.
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Male, Philippe. "Color Management System." Microscopy and Microanalysis 7, S2 (2001): 842–43. http://dx.doi.org/10.1017/s1431927600030282.
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Perception of color. in 1917, Alfred Munsell created a “notation of colors” based on the human perception of colors (Fig 1). The “tri stimuli” sensitivity of red, green and blue of the eye cones allows humans to live in an additive color space. Munsell showed that any color is defined by three components: 1-Hue, similar to different visible wavelengths. 2-Chromaticity or saturation, similar to concentration of dyes. 3-Value or brightness, representing black and white.Color Space and Gamut. Three conditions must be met to know the existence of an object, they are 1- An Illuminant (5000°K for photography), 2- An Object (Reflective, Transmissive or Emitting), 3- An Observer (Viewer, monitor, camera, detector). in 1931 La Compagnie Internationale de l’Eclairage, or CIE, met to develop a standard. This resulted in the CIE Color Space defined as a 3D volume of gamut of colors (Fig 2). Different vector notations can be used to define colors: Hue Saturation Lightness or Value (HSL or HSV), RGB (Red Green Blue), Lab (Lightness and two coordinates), and CMYK (Cyan Magenta Yellow Black).
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Sari, Filiz, and Ali Burak Ulas. "Deep Learning Application in Detecting Glass Defects with Color Space Conversion and Adaptive Histogram Equalization." Traitement du Signal 39, no. 2 (2022): 731–36. http://dx.doi.org/10.18280/ts.390238.
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Manually detecting defects on the surfaces of glass products is a slow and time-consuming process in the quality control process, so computer-aided systems, including image processing and machine learning techniques are used to overcome this problem. In this study, scratch and bubble defects of the jar, photographed in the studio with a white matte background and a -60° peak angle, are investigated with the Yolo-V3 deep learning technique. Obtained performance is 94.65% for the raw data. Color space conversion (CSC) techniques, HSV and CIE-Lab Luv, are applied to the resulting images. V channels select for preprocessing. While the HSV method decreases the performance, an increase has been observed in the CIE-Lab Luv method. With the CIE-Lab Luv method, to which is applied the adaptive histogram equalization, the maximum recall, precision, and F1-score reach above 97%. Also, Yolo-V3 compared with the Faster R-CNN, it is observed that Yolo-V3 gave better results in all analyzes, and the highest overall accuracy is achieved in both methods when adaptive histogram equalization is applied to CIE-Lab Luv.
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Luo, Yun Hui, and Mao Hai Lin. "Three-Dimensional Color Gamut Visualization of Digital Output Device Based on ICC Profile." Applied Mechanics and Materials 262 (December 2012): 36–39. http://dx.doi.org/10.4028/www.scientific.net/amm.262.36.
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As color gamut of digital output device greatly affects image appearance, accurate and effective gamut description for output device is intensively required for developing high-quality image reproduction technique based on gamut mapping. In this paper, we present a novel method to determine color gamut of output device by using a specific 3D reconstruction technology and device ICC profile. First, we populate the device color space by uniform sampling in the RGB 3-Dimensional space, and convert these sampling points to CMYK color space. Then, we work out the CIE LAB value of these points according to the ICC profile of output device. At last, in CIE LAB color space the boundary of these points is determined by using a gamut boundary descriptor based on Ball-Pivoting Algorithm (BPA) proposed by Bernardini. Compared with the results generated by ICC3D, our proposed method can compute device gamut more efficiently and at the same time give a more accurate gamut description of the output device. It will be help to develop effective gamut mapping algorithms for color reproduction.
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Xue, Yongan, Jinling Zhao, and Mingmei Zhang. "A Watershed-Segmentation-Based Improved Algorithm for Extracting Cultivated Land Boundaries." Remote Sensing 13, no. 5 (2021): 939. http://dx.doi.org/10.3390/rs13050939.
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To accurately extract cultivated land boundaries based on high-resolution remote sensing imagery, an improved watershed segmentation algorithm was proposed herein based on a combination of pre- and post-improvement procedures. Image contrast enhancement was used as the pre-improvement, while the color distance of the Commission Internationale de l´Eclairage (CIE) color space, including the Lab and Luv, was used as the regional similarity measure for region merging as the post-improvement. Furthermore, the area relative error criterion (δA), the pixel quantity error criterion (δP), and the consistency criterion (Khat) were used for evaluating the image segmentation accuracy. The region merging in Red–Green–Blue (RGB) color space was selected to compare the proposed algorithm by extracting cultivated land boundaries. The validation experiments were performed using a subset of Chinese Gaofen-2 (GF-2) remote sensing image with a coverage area of 0.12 km2. The results showed the following: (1) The contrast-enhanced image exhibited an obvious gain in terms of improving the image segmentation effect and time efficiency using the improved algorithm. The time efficiency increased by 10.31%, 60.00%, and 40.28%, respectively, in the RGB, Lab, and Luv color spaces. (2) The optimal segmentation and merging scale parameters in the RGB, Lab, and Luv color spaces were C for minimum areas of 2000, 1900, and 2000, and D for a color difference of 1000, 40, and 40. (3) The algorithm improved the time efficiency of cultivated land boundary extraction in the Lab and Luv color spaces by 35.16% and 29.58%, respectively, compared to the RGB color space. The extraction accuracy was compared to the RGB color space using the δA, δP, and Khat, that were improved by 76.92%, 62.01%, and 16.83%, respectively, in the Lab color space, while they were 55.79%, 49.67%, and 13.42% in the Luv color space. (4) Through the visual comparison, time efficiency, and segmentation accuracy, the comprehensive extraction effect using the proposed algorithm was obviously better than that of RGB color-based space algorithm. The established accuracy evaluation indicators were also proven to be consistent with the visual evaluation. (5) The proposed method has a satisfying transferability by a wider test area with a coverage area of 1 km2. In addition, the proposed method, based on the image contrast enhancement, was to perform the region merging in the CIE color space according to the simulated immersion watershed segmentation results. It is a useful attempt for the watershed segmentation algorithm to extract cultivated land boundaries, which provides a reference for enhancing the watershed algorithm.
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Tarasov, D. A., and O. B. Milder. "Mathematics and practice of color space invariants by the example of determining the gray balance for a digital printing system." Computer Optics 44, no. 1 (2020): 117–26. http://dx.doi.org/10.18287/2412-6179-co-580.
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In modern printing, a large number of tasks are associated with the mutual transformation of color spaces. In particular, the most common pair of hardware-dependent color spaces is RGB and CMYK, the mutual transformation of colors in which is ambiguous, which creates significant problems in color reproduction. To solve this problem, we propose using color space invariants — gradation trajectories and gradation surfaces, which are analogs of gradation curves for initial colorants and their binary overlays, constructed in the absolute color space of the CIE Lab. Invariants are introduced on the basis of the mathematical apparatus of the differential geometry of spatial curves and surfaces. Practical application of color space invariants involves certain difficulties associated with their complex analytical description; moreover, for most practical problems, the high accuracy of the model is redundant. For the practical application of invariants, we propose a simpler approach using natural color sampling in digital printing systems. As an example, the procedure for determining the gray balance for an electrophotographic printing press is given.
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Kuriki, Ichiro. "A Novel Method of Color Appearance Simulation Using Achromatic Point Locus With Lightness Dependence." i-Perception 9, no. 2 (2018): 204166951876173. http://dx.doi.org/10.1177/2041669518761731.
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The purpose of the present study is to propose a simple algorithm for color appearance simulation under a color illuminant. Achromatic point is a chromaticity of rays that appear neither red nor green, neither blue nor yellow under a given illuminant condition. Saturation and hue of surface colors are evaluated with respect to the achromatic point of the same lightness, while the achromatic point under a colored illuminant depends on the lightness tested. We previously found that this achromatic point locus can be simply approximated as a line with a parallel offset from the lightness axis of CIE LAB space normalized to daylight. We propose a model that applies shifts in the lightness direction after applying hue/saturation shifts using the cone-response (von Kries) transformation under an iso-lightness constraint, such that achromatic points would be aligned with the lightness axis in the CIE LAB space under daylight normalization. We tested this algorithm, which incorporates evaluation of color appearance in different lightness levels, using #theDress image. Resemblance between our simulation and subjective color-matching results implies that human color vision possibly processes shifts in color and lightness independently, as a previous study reported. Changes in the chromaticity distribution of the images were compared with conventional models, and the proposed model preserved relative color difference better, especially at the lower lightness levels. The better performance in lower lightness levels would be advantageous in displays with wider dynamic range in luminance. This implies that the proposed model is effective in simulating color appearance of images with nonnegligible lightness and color differences.
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Guo, Ying, Jun Zhang, and Tao Mo. "Contribution of Green Jadeite-Jade’s Chroma Difference Based on CIE 1976 L*a*b* Uniform Color Space." Advanced Materials Research 177 (December 2010): 620–23. http://dx.doi.org/10.4028/www.scientific.net/amr.177.620.
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The correlations between lightness and chroma, lightness difference and color difference, chroma difference and color difference were studied to evaluate the impact of lightness on color. Based on color difference formula CIE LAB in the uniform color space CIE L*a*b* it is learnt that H*ab of jadeite jade green colors has made little contribution to E*ab. Given the fact that human eyes are relatively sensitive to the color perception of lightness difference and that lightness and chroma affect each other, lightness of jadeites has been divided into two groups: while the lightness of green is relatively low (L* 19.52), lightness and chroma have positive linear correlation (correlation coefficient L* C* = 0.971), which means the higher lightness the higher chroma and brings brighter green color; while L* > 19.52 , there is no one-to-one correspondence between lightness and chroma, and the highest chroma 77.64 can be reached when L* = 37.63. The high partial correlation coefficients L*ab E*ab = 0.974 and C*ab E*ab = 0.971 reveal that both L*ab and C*ab are not affected by the lightness of jadeite and are equally important to E*ab. It is concluded that the quality estimation of green color of Jadeite Jade should be primarily based on lightness which is the most intuitive factor and consistent with the color perception, and then followed by the evaluation of chroma and hue.
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Kim, Hyun-Koo, Ju H. Park, and Ho-Youl Jung. "An Efficient Color Space for Deep-Learning Based Traffic Light Recognition." Journal of Advanced Transportation 2018 (December 6, 2018): 1–12. http://dx.doi.org/10.1155/2018/2365414.
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Traffic light recognition is an essential task for an advanced driving assistance system (ADAS) as well as for autonomous vehicles. Recently, deep-learning has become increasingly popular in vision-based object recognition owing to its high performance of classification. In this study, we investigate how to design a deep-learning based high-performance traffic light detection system. Two main components of the recognition system are investigated: the color space of the input video and the network model of deep learning. We apply six color spaces (RGB, normalized RGB, Ruta’s RYG, YCbCr, HSV, and CIE Lab) and three types of network models (based on the Faster R-CNN and R-FCN models). All combinations of color spaces and network models are implemented and tested on a traffic light dataset with 1280×720 resolution. Our simulations show that the best performance is achieved with the combination of RGB color space and Faster R-CNN model. These results can provide a comprehensive guideline for designing a traffic light detection system.
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Seo, Dae, Yong Kim, Yang Eo, and Wan Park. "Learning-Based Colorization of Grayscale Aerial Images Using Random Forest Regression." Applied Sciences 8, no. 8 (2018): 1269. http://dx.doi.org/10.3390/app8081269.
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Image colorization assigns colors to a grayscale image, which is an important yet difficult image-processing task encountered in various applications. In particular, grayscale aerial image colorization is a poorly posed problem that is affected by the sun elevation angle, seasons, sensor parameters, etc. Furthermore, since different colors may have the same intensity, it is difficult to solve this problem using traditional methods. This study proposes a novel method for the colorization of grayscale aerial images using random forest (RF) regression. The algorithm uses one grayscale image for input and one-color image for reference, both of which have similar seasonal features at the same location. The reference color image is then converted from the Red-Green-Blue (RGB) color space to the CIE L*a*b (Lab) color space in which the luminance is used to extract training pixels; this is done by performing change detection with the input grayscale image, and color information is used to establish color relationships. The proposed method directly establishes color relationships between features of the input grayscale image and color information of the reference color image based on the corresponding training pixels. The experimental results show that the proposed method outperforms several state-of-the-art algorithms in terms of both visual inspection and quantitative evaluation.
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Zhang, Mengmeng, Rongrong Ni, and Yao Zhao. "A Blind Print-Recapture Robust Watermark Scheme by Calculating Self-Convolution." International Journal of Digital Crime and Forensics 11, no. 4 (2019): 28–49. http://dx.doi.org/10.4018/ijdcf.2019100103.
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A blind print-recapture robust watermark scheme is proposed. Watermark patterns are embedded into the space domain of a color image and can be detected from a print-recaptured version of the image without knowledge of the original image. The process of embedding invisible watermarks to convert RGB color images to CIE Lab color spaces and embed periodic watermarks in both color channels at the same time. Watermark extraction is achieved by calculating self-convolution and inverting the geometric transformation such as rotation and scale. Normalized correlation coefficients between the extracted and the embedded watermark pattern is calculated to determine whether there is watermark. The decision about the presence/absence of the watermark pattern is then determined by a threshold which is set 0.13, and the detection rate of 241 pictures is about 0.79.
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Poynton, Charles, Robin Atkins, Jaclyn Pytlarz, and Dale Stolitzka. "18‐3: Computing Display Color Gamut Volume using Tetrahedra." SID Symposium Digest of Technical Papers 54, no. 1 (2023): 229–32. http://dx.doi.org/10.1002/sdtp.16532.
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We describes an approach to computation of display color gamut volume (sometimes called color volume). We describe two methods of partitioning color space into tetrahedra, and methods of aggregating the volume of tetrahedra. There some mathematical subtleties that need to be addressed to efficiently obtain the correct result. We discuss the constraints that guide a suitable choice of color space in which to perform the calculation. Our goal is to characterize the range of physical stimuli produced by a display. We want a perceptual measure of this volume, but we want the metric to cover the entire range of physical display stimuli, not just the range attained at a particular state of the viewer's adaptation. We comment on using CIE LAB or BT.2124 ITP5 as the underlying colorspace, and suggest that ITP is most useful.
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Kim, Sung Joon, and Kyung Won Baek. "Application of color science in dentistry." Journal of Medicine and Life Science 7, no. 2 (2010): 7–12. http://dx.doi.org/10.22730/jmls.2010.7.2.7.
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The color and appearance of teeth and oral structures are a complex phenomenon, with many factors such as lighting conditions, translucency, opacity, light scattering, gloss and the human eye and brain influencing the overall perception of tooth color. In clinical practice and research, measurements of the color of natural tooth, gingiva, restorative craniofacial and dental materials are important and applicable to many field. The application of color science in dentistry has enabled the measurement of tooth color in an objective way, with the most common color space in current use being CIE Lab system. This article will provide the color science pertinent to teeth and maxillofacial structure and measurement with geometrical aspects of measuring systems. Also, the article includes the color difference and perception aspects of tooth color together with a review of the range of tooth color measured in different populations.
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Chandrakanth, T., and B. Sandhya. "Analysis of SSIM based Quality Assessment across Color Channels of Images." International Journal of System Dynamics Applications 4, no. 3 (2015): 30–42. http://dx.doi.org/10.4018/ijsda.2015070102.
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Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.
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Hyunjoo, Ahn, and Lee Sangwon. "The Impact of Color on 2D Motion Illusion Design -Focused on Color Elements and Proximity Model within the CIE Lab Color Space-." JOURNAL OF THE KOREAN SOCIETY DESIGN CULTURE 30, no. 3 (2024): 239–53. http://dx.doi.org/10.18208/ksdc.2024.30.3.239.
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Wiśniewska, Kornelia, Ewelina Kłosek-Wawrzyn, Radosław Lach, and Waldemar Pichór. "Influence of the Grain Size Distribution of the Limestone Additives on the Color Properties and Phase Composition of Sintered Ceramic Materials Based on Cream-Firing Clays." Materials 15, no. 7 (2022): 2694. http://dx.doi.org/10.3390/ma15072694.
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The study focused on determining color changes in materials made of cream-firing clays from the Opoczno region (Poland) due to the addition of calcium carbonate in the form of limestone. Moreover, the influence of the grain size distribution of this additive on the color properties of the materials and their phase composition was determined. Test samples were prepared using theplastic method and fired at four different temperatures: 1120, 1140, 1160 and 1180 °C. The color properties of the surface of ceramic materials were determined in CIE-Lab color space using a colorimeter. Quantitative phase analysis was performed using the Rietveld method. The research showed that the addition of calcium carbonate causes an increase in the yellow color factor and a decrease in the red color factor and the brightness of the material. Moreover, it was proven that the grain size distribution of the additive used significantly influences the phase composition of the materials, thus determining the values of physical properties and the color of the materials.
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Naik, Dayakar L., Hizb Ullah Sajid, Ravi Kiran, and Genda Chen. "Detection of Corrosion-Indicating Oxidation Product Colors in Steel Bridges under Varying Illuminations, Shadows, and Wetting Conditions." Metals 10, no. 11 (2020): 1439. http://dx.doi.org/10.3390/met10111439.
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Early detection of corrosion in steel bridges is essential for strategizing the mitigation of further corrosion damage. Although various image-based approaches are available in the literature for corrosion detection, most of these approaches are tested on images acquired under uniform natural daylight illuminations i.e., inherent variations in the ambient lighting conditions are ignored. Owing to the fact that varying natural daylight illuminations, shadows, water wetting, and oil wetting are unavoidable in real-world scenarios, it is important to devise a robust technique for corrosion identification. In the current study, four different color spaces namely ‘RGB’, ‘rgb’, ‘HSV’ and ‘CIE La*b*’ along with a multi-layer perceptron (MLP) is configured and trained for detecting corrosion under above-mentioned real-world illumination scenarios. Training (5000 instances) and validation (2064 instances) datasets for this purpose are generated from the images of corroded steel plates acquired in the laboratory under varying illuminations and shadows, respectively. Each combination of color space and an MLP configuration is individually assessed and the best suitable combination that yields the highest ‘Recall’ value is determined. An MLP configuration with a single hidden layer consisting of 4 neurons (1st Hidden Layer (HL)(4N)) in conjunction with ‘rgb’ color space is found to yield the highest ‘Accuracy’ and ‘Recall’ (up to 91% and 82% respectively). The efficacy of the trained MLP to detect corrosion is then demonstrated on the test image database consisting of both lab-generated partially corroded steel plate images and field-generated images of a bridge located in Moorhead (Minnesota). Lab-generated images used for testing are acquired under varying illuminations, shadows, water wetting, and oil wetting conditions. Based on the validation studies, ‘rgb’ color space and an MLP configuration consisting of single hidden layer with 4 neurons (1st HL(4N)) trained on lab-generated corroded plate images identified corrosion in the steel bridge under ambient lighting conditions.
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Culic, Bogdan, Vasile Prejmerean, Cristina Gasparik, Carina Culic, Cristian Dragos, and Diana Dudea. "In Vitro Evaluation of New Dental Software for Shade Matching." Key Engineering Materials 587 (November 2013): 360–65. http://dx.doi.org/10.4028/www.scientific.net/kem.587.360.
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In this study we evaluate a new computer software developed for determining tooth color parameters obtained from digital images taken in a general practice working conditions. In order to evaluate the accuracy of the program, we used as samples dental shade tabs. The tabs were measured using a dental spectrophotometer, and then photographed and measured using our program (Toodent). L, a, b values of the CIE Lab color space were obtained. The results were also automatically expressed in dental shade tab code. The results analysis was made by comparing the L, a, b values obtained by the program, with spectrophotometer ones taken from the same shade tab. A statistical indicator was created in order to evaluate the accuracy of the program. Further evaluation of the program shall be made, in order to be used in routine clinical color selection.
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Du, Yang, and Ying Guo. "Study on the Chromogenic Mechanism of Violet-Red to Orange-Red Spinel." Crystals 13, no. 2 (2023): 339. http://dx.doi.org/10.3390/cryst13020339.
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In this paper, the chemical composition and spectroscopy of 38 violet-red to orange-red spinel samples were analyzed by energy dispersive X-ray fluorescence spectrometer and UV-visible spectrophotometer, based on CIE LAB color space, to explore the effects of different chromogenic ions on spinel color transition. The results show that the chroma C* is mainly controlled by the variation of color coordinates a*, and the hue angle h° is mainly controlled by the variation of color coordinates b*. Spinel can be divided into iron-bearing spinel and chromium–vanadium-bearing spinel according to their chromogenic elements, where Fe is mostly present in the form of Fe2+, which is mainly replaced with Mg2+ in tetrahedral voids, while Cr3+ and V3+ are mainly replaced with Al3+ in octahedral voids, and the level of Al content indicates the degree of isomorphism in spinel. The lightness L* of spinel decreases with increasing Cr content, and the hue h° decreases with increasing Fe and increases with increasing V content.
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Liu, Ziming, Danpei Zhao, Zhenwei Shi, and Zhiguo Jiang. "Unsupervised Saliency Model with Color Markov Chain for Oil Tank Detection." Remote Sensing 11, no. 9 (2019): 1089. http://dx.doi.org/10.3390/rs11091089.
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Traditional oil tank detection methods often use geometric shape information. However, it is difficult to guarantee accurate detection under a variety of disturbance factors, especially various colors, scale differences, and the shadows caused by view angle and illumination. Therefore, we propose an unsupervised saliency model with Color Markov Chain (US-CMC) to deal with oil tank detection. To avoid the influence of shadows, we make use of the CIE Lab space to construct a Color Markov Chain and generate a bottom-up latent saliency map. Moreover, we build a circular feature map based on a radial symmetric circle, which makes true targets to be strengthened for a subjective detection task. Besides, we combine the latent saliency map with the circular feature map, which can effectively suppress other salient regions except for oil tanks. Extensive experimental results demonstrate that it outperforms 15 saliency models for remote sensing images (RSIs). Compared with conventional oil tank detection methods, US-CMC has achieved better results and is also more robust for view angle, shadow, and shape similarity problems.
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SREELEKHA, G., and P. S. SATHIDEVI. "A WAVELET-BASED PERCEPTUAL IMAGE CODER INCORPORATING A NEW MODEL FOR COMPRESSION OF COLOR IMAGES." International Journal of Wavelets, Multiresolution and Information Processing 07, no. 05 (2009): 675–92. http://dx.doi.org/10.1142/s0219691309003197.
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A wavelet-based perceptual image coder for the compression of color images is proposed here in which the coding structure is coupled with Human Visual System models to produce high quality images. The major contribution is the development of a new model for the compression of the color components based on psychovisual experiments, which quantifies the optimum amount of compression that can be applied to the color components for a given rate. The model is developed for YCbCr color space and the perceptually uniform CIE Lab color space. A complete coding structure for the compression of color images is developed by incorporating the new perceptual model. The performance of the proposed coder is compared with a wavelet-based coder that uses the quantization stage of the JPEG2000 standard. The perceptual quality of the compressed images is tested using the wavelet-based subjective and objective perceptual quality matrices such as Mean Opinion Score, Visual Information Fidelity and Visual Signal to Noise Ratio. Though the model is developed for a perceptually lossless high quality image compression, results obtained reveal that the proposed structure gives very good perceptual quality compared to the existing schemes for lower bit rates. These advantages make the proposed coder a candidate for replacing the encoder stage of the current image compression standards.
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Tang, Wei Xi, Ying Guo, and Li Xia Ma. "Influence of Fe2+ on the Color Appearance of Yellow-Green Peridot." Key Engineering Materials 492 (September 2011): 370–73. http://dx.doi.org/10.4028/www.scientific.net/kem.492.370.
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Twenty-eight yellow-green color of uniform, high clarity and similar thickness of 5 mm × 7 mm oval faceted peridots from Jiaohe Jilin province were examined by LA-ICP-MS and Color i5 to test their chemical compositions and L*, C* and ho. The correlations between Fe2+ and color parameters were analyzed, in order to establish the influence on the color appearance of Fe2+. The chemical formula of the twenty-eight peridots is (Mg1.84,Fe0.19)2.04[(Si0.982,Al0.001)0.983O4], which was calculated by oxygen atom. It reveals that 0.19 mol Fe2+ is concluded in one mol peridot, and Fe2+ is the colorant of peridot. Based on the CIE 1976 L*a*b* uniform color space, relationships between chromaticity coordinates a*, b* and chromaticity C* were analyzed by Two-way ANOVA, of which the results showing that the influence of b* on C* (rb*×C*=0.996) is much more prominent than a* on C* (ra*×C*= -0.383). By partial correlation analysis of the results calculated through CIE LAB color-difference formula, it can be discovered that lightness difference DL* has a better correlation with chromatic aberration DE* than DC* and DH*, whereas the significance level ρDC*×DE* > 0.05, rDH*×DE* > 0.05, it reveals that DE* is more sensitive to DL*. At the same time, L* changes the most with the contributions of Fe2+ compared with other parameters of peridot. It is concluded that, with the help of L*, Fe2+ has a further influence on the color appearance of peridot.
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Zainuddin, Bunyamin, Elkawakib Syam’un, Muhammad Azrai, and Yunus Musa. "Prediction of Normalized Difference Vegetation Index and Spad Chlorophyll Under High Maize Population Density." BIO Web of Conferences 158 (2025): 03001. https://doi.org/10.1051/bioconf/202515803001.
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The study investigates the relationship between the Normalized Difference Vegetation Index (NDVI), SPAD reading and visible color spectra under high maize population density. Utilizing machine learning techniques and RGB colorimeter data from the CIE Lab color space, predictive models for NDVI and SPAD values were developed. The study, conducted at the Bajeng Research Station in South Sulawesi, Indonesia, spanned from October 2023 to January 2024. The experiment involved 78 hybrid maize candidates and five commercial varieties cultivated at a high-density setting of 83,333 plants per hectare. NDVI and SPAD measurements were conducted between 46-52 days post-planting using GreenSeeker and SPAD Konica Minolta devices respectively. Additionally, leaf color data were captured using a commercial LAB colorimeter. A decision tree-based machine learning algorithm was employed for data processing. Results indicate strong predictive capabilities of tree-based machine learning models in predicting NDVI, with a significant association between color components and NDVI. Combining L, A, and B as input features notably improves the model’s performance with an R2 value of 0.862, MAE = 0.018, RMSE = 0.023, and MPE = 0.001, underscoring the importance of integrating multiple color channels for comprehensive vegetation characterization. As for SPAD prediction, the machine learning model also exhibits promising results, with an R2 value of 0.686, MAE = 2.327, RMSE = 3.175, and MPE = 10.081. Integrating visible spectral data from a colorimeter with decision tree algorithms could serve as an alternative approach for assessing plant health.
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Shi, Rui Zhi, Kai Bo Fan, Xiao Zhou, Kun Yang, and Han Zhong Shi. "Study on the Model of Chromaticity Closed-Loop Control for Print Online Detection." Applied Mechanics and Materials 262 (December 2012): 291–96. http://dx.doi.org/10.4028/www.scientific.net/amm.262.291.
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The print online detection technology contains wide range of content, for instance alignment inspection, defect detection and color detection, among them the color detection is the most difficult. In this paper, IGT printability tester is used to produce different ink film thickness samples of the yellow, magenta, cyan, black and map spot colors brown, blue, green, red, purple and other colors. Based on large number of experiment data collected, though mathematical modeling, data analysis, experimental validation and model updating, a closed-loop control model and techniques based on the chromaticity detection are proposed. By establishing the model of the relationship between the chromaticity value and the ink film thickness, the relationship between the ink film thickness and the ink key opening, the numerical calculation between the chromaticity and the ink key opening is achieved. The basic method of chromaticity closed-loop control is: when printing began, the model calculates the initial ink key opening with the ink preset algorithm, and set the ink key opening. After entering the print state, the model detects the RGB value of print by the machine vision technology, and converts the RGB value to CIE LAB values by color space conversion and gamut mapping. Then the model compares the Lab values with the standard values, determines whether the color-difference overrun. If the color-difference is within the allowable range, the model maintains the original amount of ink and ink key opening. If it exceeds the limit value, the model quickly calculates the deviation of the ink amount, and offers the ink key opening which is corresponding to the adjustment, feedbacks it to the print control center, resulting in the ink key response in order to achieve the real-time adjustment of the print ink amount. Compared with the control method of the ink amount based on density detection, the chromatic detection method is more accurate, and has better application prospects.
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Wang, Xiujuan, Liang Mao, and Ji Wang. "Underwater fish image enhancement method based on color correction." Highlights in Science, Engineering and Technology 1 (June 14, 2022): 415–25. http://dx.doi.org/10.54097/hset.v1i.498.
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Due to the absorption and scattering of light propagation underwater, the captured underwater images often have problems such as color bias, low contrast and poor clarity, resulting in low accuracy of underwater fish identification. To address this problem, this paper proposes an underwater fish image enhancement method based on color correction to enhance the acquired fish images and improve the accuracy of fish target recognition. Firstly, color correction is achieved by stretching the L component and changing the a and b components of the CIE-Lab color space to improve image sharpness. Then the colors of the R-G-B channels of the image are equalized to reduce the color bias. Finally, the histograms of the three R-G-B channels are redistributed. Comparison experiments were conducted with existing methods on a self-built fish image dataset, and the enhanced images were analyzed from both subjective and objective evaluations. The results showed that the enhancement effect of the method in this paper is better than other methods. Finally, the comparison experiments of target recognition before and after image enhancement were conducted on YOLOv5, and the results showed that the enhanced image target recognition accuracy was 99.8%, which was 1.2 percentage points higher than that before enhancement; the average accuracy mAP was 94.5%, which was 5.6 percentage points higher than that before image enhancement. The method in this paper can effectively improve the problems of underwater images and provide technical support for underwater target recognition.
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Kusuma, Edi Jaya, Ika Pantiawati, and Sri Handayani. "Melanoma Classification based on Simulated Annealing Optimization in Neural Network." Knowledge Engineering and Data Science 4, no. 2 (2022): 97. http://dx.doi.org/10.17977/um018v4i22021p97-104.
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Technology development in image processing and artificial intelligence field leads to the high demand for smart systems, especially in the health sector. Cancer is one of the diseases that has the highest mortality cases around the world. Melanoma is one of the cancer types that appear caused by high exposure to UV light. The earliest the melanoma was identified, the higher the chance the patient can be recovered. Therefore, this study carries the melanoma detection based on BPNN optimized by a simulated annealing algorithm. This research utilizes PH2 dermoscopic image data which contains 200 color digital images in BMP format. The data is processed using color feature extraction techniques to identify the characteristics of each image according to the target data. The color space extraction used includes mean RGB, HSV, CIE LAB, YCbCr, and XYZ. The evaluation result showed that the BPNN-SA method was able to increase the accuracy performance in classifying skin cancer when compared to the original BPNN method with an overall average accuracy of 84.03%.
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Du, Yuting, Tong Qiao, Ming Xu, and Ning Zheng. "Towards Face Presentation Attack Detection Based on Residual Color Texture Representation." Security and Communication Networks 2021 (March 15, 2021): 1–16. http://dx.doi.org/10.1155/2021/6652727.
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Most existing face authentication systems have limitations when facing the challenge raised by presentation attacks, which probably leads to some dangerous activities when using facial unlocking for smart device, facial access to control system, and face scan payment. Accordingly, as a security guarantee to prevent the face authentication from being attacked, the study of face presentation attack detection is developed in this community. In this work, a face presentation attack detector is designed based on residual color texture representation (RCTR). Existing methods lack of effective data preprocessing, and we propose to adopt DW-filter for obtaining residual image, which can effectively improve the detection efficiency. Subsequently, powerful CM texture descriptor is introduced, which performs better than widely used descriptors such as LBP or LPQ. Additionally, representative texture features are extracted from not only RGB space but also more discriminative color spaces such as HSV, YCbCr, and CIE 1976 L∗a∗b (LAB). Meanwhile, the RCTR is fed into the well-designed classifier. Specifically, we compare and analyze the performance of advanced classifiers, among which an ensemble classifier based on a probabilistic voting decision is our optimal choice. Extensive experimental results empirically verify the proposed face presentation attack detector’s superior performance both in the cases of intradataset and interdataset (mismatched training-testing samples) evaluation.
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Aydın Atasoy, Nesrin, and İrem Kura. "CLASSIFICATION OF X-RAY AND CT IMAGES IN DIFFERENT COLOR SPACES USING ROBUST CNN." Mühendislik Bilimleri ve Tasarım Dergisi 12, no. 3 (2024): 505–16. http://dx.doi.org/10.21923/jesd.1415150.
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Since deep learning models have been successfully used in many fields, they have been used to identify sick and healthy people in X-ray or Computed Tomography (CT) chest radiology images. In this study, Covid-19 and pneumonia classification is performed on both X-ray and CT images using the robust Convolutional Neural Network (CNN). BGR, HSV, and CIE LAB color space transformations are applied to X-ray and CT images to show that the model performs a successful classification independent of dataset characteristics. The binary classification accuracy rates of Covid-19 and pneumonia for X-ray images and CT images are 98.7% and 98.4%, 97.6% and 99.4%, respectively. Precision, Recall, Specificity, F1 score, and Mean Squared Error metrics are calculated for each X-ray and CT dataset. In addition, 5-fold cross-validation proved accuracy of the model. Although X-ray and CT chest radiology images are transformed into different color spaces, the proposed model performed a successful classification. Thus, even if the image characteristics of the radiology device brands change, the computer-based system will be able to make successful disease diagnoses at low cost where expert personnel are insufficient.
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Al Hakeem, Zahraa, Haider Ismael, and Hawraa Abbas. "An Automatic System for Smoke Detection in Outdoor Areas." Kerbala Journal for Engineering Sciences 3, no. 1 (2023): 15–31. https://doi.org/10.63463/kjes1069.
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Early detection of fires plays a crucial role in minimizing their impact and preventing them from spreading. Every year, the repetition of fires results in the loss of human life, animal life, and plant life. Fire detection has become increasingly desirable and significant in surveillance systems, where traditional methods of detecting smoke relied on smoke sensors. Therefore, this method is ineffective in open and large buildings, and outdoor areas. As a result, this study suggests using computer vision systems to detect smoke in open spaces by using a static camera. To reduce the data size while preserving important details, the input video is framed and decomposed using the Integer Haar Lifting Wavelet Transform (IHLWT). Then, for smoke color detection, a new method called the multi-threshold International Commission on Illumina (CIE) Lab color space is used, which took into account the smoke colors' change from whitish gray to blackish gray. In addition, the Frame Differences (FD) technique is used to detect motion and thus reduce false alarms. The smoke color detection is combined with frame difference techniques. The small pixels are removed via a morphological operation that represents noise. According to the experimental findings, the approach precision for offline videos is greater than 94.7% for eleven videos, while the average detection reaches 92.8% for online (real time) videos. It also reduces false alarms significantly. According to the trials and comparisons, the suggested smoke detection algorithm performs better than the traditional algorithms in many scenarios. It is also simple, efficient, and low in complexity.
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Mohamed, Hassan, Kazuo Nadaoka, and Takashi Nakamura. "Automatic Semantic Segmentation of Benthic Habitats Using Images from Towed Underwater Camera in a Complex Shallow Water Environment." Remote Sensing 14, no. 8 (2022): 1818. http://dx.doi.org/10.3390/rs14081818.
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Underwater image segmentation is useful for benthic habitat mapping and monitoring; however, manual annotation is time-consuming and tedious. We propose automated segmentation of benthic habitats using unsupervised semantic algorithms. Four such algorithms––Fast and Robust Fuzzy C-Means (FR), Superpixel-Based Fast Fuzzy C-Means (FF), Otsu clustering (OS), and K-means segmentation (KM)––were tested for accuracy for segmentation. Further, YCbCr and the Commission Internationale de l’Éclairage (CIE) LAB color spaces were evaluated to correct variations in image illumination and shadow effects. Benthic habitat field data from a geo-located high-resolution towed camera were used to evaluate proposed algorithms. The Shiraho study area, located off Ishigaki Island, Japan, was used, and six benthic habitats were classified. These categories were corals (Acropora and Porites), blue corals (Heliopora coerulea), brown algae, other algae, sediments, and seagrass (Thalassia hemprichii). Analysis showed that the K-means clustering algorithm yielded the highest overall accuracy. However, the differences between the KM and OS overall accuracies were statistically insignificant at the 5% level. Findings showed the importance of eliminating underwater illumination variations and outperformance of the red difference chrominance values (Cr) in the YCbCr color space for habitat segmentation. The proposed framework enhanced the automation of benthic habitat classification processes.
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Yang, Sungjun, Seungyong Shin, Heonji Ha, and Sangmoon Park. "Nonstoichiometric LaO0.65F1.7 Structure and Its Green Luminescence Property Doped with Bi3+ and Tb3+ Ions for Applying White UV LEDs." Materials 15, no. 12 (2022): 4222. http://dx.doi.org/10.3390/ma15124222.
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Red–green–blue phosphors excited by ultraviolet (UV) radiation for white light LEDs have received much attention to improve the efficiency, color rendering index (CRI), and chromatic stability. The spectral conversion of a rare-earth ion-doped nonstoichiometric LaO0.65F1.7 host was explored with structural analysis in this report. The nonstoichiometric structure of a LaO0.65F1.7 compound, synthesized by a solid-state reaction using La2O3 and excess NH4F precursors, was analyzed by synchrotron X-ray powder diffraction. The crystallized LaO0.65F1.7 host, which had a tetragonal space group of P4/nmm, contained 9- and 10-coordinated La3+ sites. Optical materials composed of La1−p−qBipTbqO0.65F1.7 (p = 0 and 0.01; q = 0–0.2) were prepared at 1050 °C for 2 h, and the single phase of the obtained phosphors was indexed by X-ray diffraction analysis. The photoluminescence spectra of the energy transfer from Bi3+ to Tb3+ were obtained upon excitation at 286 nm in the nonstoichiometric host lattice. The desired Commission Internationale de l’Eclairage (CIE) values of the phosphors were calculated. The intense green La0.89Bi0.01Tb0.1O0.65F1.7 phosphor with blue and red optical materials was fabricated on a 275 nm UV-LED chip, resulting in white light, and the internal quantum efficiency, CRI, correlated color temperature, and CIE of the pc LED were characterized.
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Behera, Debendra, and Dr Neelam rout. "Image Pattern Analysis Using Hybrid Feature Descriptors for Content-Based Image Retrieval." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51301.
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Content-Based Image Retrieval (CBIR) has emerged as a vital technique for efficient image indexing and retrieval in large-scale databases. Traditional approaches often rely on handcrafted features such as color, texture, and shape, which are limited in capturing high-level semantic information. On the other hand, deep learning-based descriptors have shown significant improvement in extracting abstract features but often require large datasets and computational resources. This paper proposes a hybrid CBIR framework that fuses deep learning-based RGB image features with texture-based descriptors such as Local Binary Patterns (LBP), Center Symmetric LBP (CSLBP), and Local Directional Patterns (LDP). The hybrid descriptors are extracted using dual convolutional neural network (CNN) encoders, each trained on RGB and texture images independently. Additionally, a weighted feature fusion technique in the CIE Lab* color space is presented to emphasize salient regions of images, enhancing retrieval precision. The system is evaluated on standard benchmark datasets including Corel-1K, Caltech-256, and 102Flower, and achieves superior performance in terms of precision, recall, and F1-score. The experimental results demonstrate that hybrid feature fusion significantly improves retrieval accuracy compared to traditional and single-feature descriptors.
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Jung, Sang-Bin, and Ji-Yeon Jang. "Surface Color and Dyeing Amount of Natural Hair Dyeing Using Cochineal." Journal of the Korean Society of Cosmetology 30, no. 6 (2024): 1503–11. https://doi.org/10.52660/jksc.2024.30.6.1503.
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This study analyzed the effects of mordants (alum, red clay, and salt) and dyeing temperatures (20°C, 40°C, 50°C, 60°C) on the natural dyeing of hair using cochineal. Hair samples were dyed according to combinations of each mordant and dyeing temperature, and the colors were measured using the CIE Lab* color space. The dye uptake was quantified using the K/S value. The experimental results showed that compared to the raw samples, the L*value decreased and the a* value increased under all dyeing conditions, indicating a more vivid color. At 20°C with alum, the L*value was 70.01, the a* value was 18.34, and the K/S value was 21.91, demonstrating the highest dye uptake. Red clay and salt also exhibited significant dye uptake with K/S values of 22.54 and 22.87, respectively. At 40°C with alum, the L*value decreased to 61.03, while the K/S value increased to 31.14. The K/S values for alum continued to rise at 50°C and 60°C, reaching 35.14 and 35.46, respectively. In contrast, red clay and salt showed relatively lower K/S values, but there was a trend of improved dye uptake with increasing dyeing temperatures. In conclusion, the combination of mordants and dyeing temperatures significantly affects dye uptake and color in natural hair dyeing with cochineal. Notably, using alum achieves high dye uptake. This study provides foundational data that can contribute to the optimization of natural dyeing and suggests the need for further research on combinations with various natural dyes and changes in the physical properties of hair after dyeing.
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Pechyen, Chiravoot, Calin Trif, Benya Cherdhirunkorn, Surachet Toommee, and Yardnapar Parcharoen. "Measurement of Ellman’s Essay Using a Smartphone Camera Coupled with an Image Processing Technique in CIE-LAB Color Space for the Detection of Two Pesticides in Water." Analytica 6, no. 1 (2025): 4. https://doi.org/10.3390/analytica6010004.
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In recent years, Thailand’s agriculture sector has seen a significant rise in pesticide usage due to its vital role in the economy and global food trade. However, the uncontrolled use of pesticides poses severe health and environmental risks. This research focuses on the detection of pesticide residues, particularly carbaryl and paraoxon-ethyl, which are prevalent due to their high efficacy in pest control but pose neurological health risks by inhibiting acetylcholinesterase (AChE) activity, potentially impacting human health. The developed method assesses pesticide concentration by measuring changes in the CIE-LAB color space using a smartphone camera. Testing several concentrations (0.2, 0.6, and 1.0 ppm) over time revealed significant differences via ANOVA (F = 32.8, p < 0.001) and a strong linear relationship with R2 values from 0.9129 to 0.9973 through regression analysis. Additionally, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were utilized to further understand the relationship between color changes and pesticide type and concentration. PCA showed that the L* and b* values contributed most to explaining the variance in the data (96.24%), while PLS-DA provided classification models. These strong linear relationships between pesticide concentration and colorimetric changes showcase the method’s accuracy and potential for on-site pesticide monitoring in agricultural produce, emphasizing technological advancements in sustainable agriculture practices. This research presents encouraging findings from an inexpensive and straightforward method for detecting pesticide residues, suggesting that a specialized mobile application could enhance the implementation of the proposed system.
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Aleinikov, A. F. "METHOD OF NON-INVASIVE DETERMINATION OF FUNGAL DISEASES OF COMMON GARDEN STRAWBERRY." Siberian Herald of Agricultural Science 48, no. 3 (2018): 71–83. http://dx.doi.org/10.26898/0370-8799-2018-3-10.
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The relevance of early undamaging diagnosis of fungal, viral and bacterial diseases of common garden strawberry is proved. External symptoms of fungal diseases are given. On the basis of literature data, the existing optical methods of early diagnostics of cultivated plants are analyzed. It is established that the methods of pixel calculation of the image in the space of color channels of red, green and blue colors are more preferable than other optical methods for detection of strawberry fungal diseases. This results from the fact that fungal diseases create specific color spots and their distribution on the surface of a plant can be easily identified in the colorimetric CIE Lab system. The work presents a number of approaches to the new method of early diagnostics of common garden strawberry fungal diseases with use of technical means and software developed for the smartphone. Implementation of the method does not require big expenses as it is done in the form of the software application in the smartphone on the basis of the Android operating system. This application will enable to obtain high quality images of a leaf of a plant, it will also provide segmentation and calculation of the quantity and the specific area of color spots on a contour of a leaf. Moreover, it will work with the database of model images of plants with fungal diseases. Classification of fungal diseases and forecasting of their development will be carried out by means of artificial neural network. The proposed method will allow to determine diseases of common garden strawberry leaves, to predict their development and to establish possible borders of distribution on the chosen plantation.
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Indriatmoko, Indriatmoko, Dimas A. Hedianto, Sari Budi Moria, and Didik WH Tjahjo. "Coloration Characteristic and Population Genetic Analysis of Wild-Captured Giant Tiger Shrimp (Penaeus monodon) from Aceh Timur." ILMU KELAUTAN: Indonesian Journal of Marine Sciences 23, no. 3 (2018): 123. http://dx.doi.org/10.14710/ik.ijms.23.3.123-130.
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Giant tiger shrimp (Penaeus monodon) has become a prime commodity in Indonesia which was produced by aquaculture and capture fisheries activities. Aceh Province, in this case mostly represented by Aceh Timur District, was well-known as the center of wild-captured-adult giant tiger shrimp. Several previous investigations had proved for its high-quality shrimp spawner in producing good eggs in quality and quantity under artificial spawning condition. Two main interesting points of wild giant tiger shrimp from Aceh Timur came from their coloration and population clusters. This report was aimed to provide that information pre-preliminary and highlighted quantitative information of coloration characteristic through RGB (Red Green Blue) and CIE Lab color space data analysis, as well as, 16S rDNA-PCR-RFLP genetic comparison among four population clusters in Aceh Timur Waters. The color analysis resulted in significant differences between wild-captured and pond-cultured giant tiger shrimp which produced R value 0.1524±0.0091 and 0.1268±0.0004, respectively. Total pixel analysis through L* a* b* color space has distinguished detailed differentiation between wild-captured and pond-cultured giant tiger shrimp acquired images. It is known that most of the wild-captured image pixels were concentrated in quadrant I (+a, +b) while pond-cultured in quadrant II (-a, +b) and III (-a, -b).Genotyping of represented samples from 4 population clusters, i.e. Aceh Tamiang, Langsa, Peudawa, and Julok produce 2 haplotype composite, AAA and AAB. Among 4 clusters, it was found that Julok has become the only cluster which has a different haplotype composite ratio (1:1) (D 0.0348, V 0,9501) from the others (4:1)(V 0.9504).
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Wiśniewska, Kornelia, Waldemar Pichór, and Ewelina Kłosek-Wawrzyn. "Influence of Firing Temperature on Phase Composition and Color Properties of Ceramic Tile Bodies." Materials 14, no. 21 (2021): 6380. http://dx.doi.org/10.3390/ma14216380.
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This study is focused on the behavior of the cream-firing clays from Opoczno region (Poland). The ceramic masses on which tests were carried out consisted of cream-firingBorkowice clay and dolomite in two different grain sizes as an additive that changes the color of ceramic materials. Test samples were prepared by plastic method and fired at range of 1100–1240 °C. Phase composition of theinvestigated materials was characterized by XRD method with quantitive analysis of the amorphous phase determined by the Retvield technique. Color properties of the surface of the obtained ceramic materials were determined in CIE-Lab color space. The phase composition of the obtained ceramics depends on the firing temperature. The color of the surface of the ceramic materials also depends on the firing temperature. There was a tendency to decrease the brightness, decrease the blue shade, and increase the yellow shade of the surface of materials with increasing the temperature. The conducted tests allowed to conclude that the color of ceramic materials depends on their phase composition. The most important role in the formation of color correspond to the amorphous phase, formed during the process. The lower content of the amorphous phase in the material allows to obtain brighter products with a lower proportion of yellow, and therefore closer to white. Moreover, following tests were carried out: total water absorption, total open porosity, linear shrinkage, and flexural strength. With increasing the temperature, total water absorption and total open porosity decrease, and total linear shrinkage increases due to the progressive sintering process. Flexural strength increases with the increase of the firing temperature for materials consisting of Borkowice clay. The addition of dolomite introduced new pores into the material, which resulted in an increase in flexural strength at lower firing temperatures and a decrease in flexural strength at higher firing temperatures.
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Suryasari, Suryasari, Aminuddin Rizal, Sri Kusumastuti, and Taufiqqurrachman Taufiqqurrachman. "Illuminance Color Independent in Remote Photoplethysmography for Pulse Rate Variability and Respiration Rate Measurement." JOIV : International Journal on Informatics Visualization 7, no. 3 (2023): 920. http://dx.doi.org/10.30630/joiv.7.3.1176.
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Remote photoplethysmography (rPPG) is now becoming a new trend method to measure human physiological parameters. Especially due to it noncontact measurement which safe dan suitable to use in this new era condition. Pulse rate variability (PRV) and respiration rate (RR) included as parameters can be measured by using rPPG. PRV and RR are used to measure both physical and psychological wellness of the subject. However, current performance challenges in rPPG algorithm in measuring PRV and RR are illuminance invariant and motion. Especially in different light condition which represent real-life environment, signal-to-noise ratio (SNR) will be affected and directly reduce the measurement accuracy. Therefore in this study, we develop rPPG algorithm and then investigate the performance rPPG in different illuminance scenarios. We perform PRV and RR measurement under each scenario. On this study, for the pulse signal extraction, we were using algorithm is based on the modification of plane orthogonal-to-skin (POS) algorithm. While, for respiration signal extraction is done in CIE Lab color space. Our experimental results show the mean absolute error (MAE) of each measured parameters are 3.25 BPM and 2 BPM for PRV and RR respectively compared with clinical apparatus. The proposed method proved to be more reliable to use in real environments measurement. However, limitation of our proposed algorithm is still running in offline mode, hence for the future we want try to make our algorithm run in real time.
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Abu-Alruz, Khaled. "Quality of White-Brined Nabulsi Cheese Made with Different Proportions of Sheep’s and Cows’ Milk." Current Research in Nutrition and Food Science Journal 11, no. 1 (2023): 88–110. http://dx.doi.org/10.12944/crnfsj.11.1.6.
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Nabulsi cheese is the dominant white-brined cheese in Jordan and neighboring countries. Although this cheese is typically prepared using sheep’s milk, achieving large-scale production or attaining a specific quality involves the use of cows’ milk. Nabulsi cheese is kept in >18% brine for up to 1 year at room temperature (25 °C) and then soaked in water for desalting before eating. In this study, the effects of the milk type/combination used for production (100% sheep’s milk; 100% cows’ milk; 1:1, 3:1, or 1:3 sheep’s:cows’ milk mixture), desalting (salted vs. desalted cheese), and storage time (0, 6, and 12 months) on the cheese’s chemical composition directly after processing (in the salted form), texture (according to texture profile analysis “TPA”), and color (according to CIE lab color space) were assessed. The type or the combination of milk used does not affect the chemical composition of Nabulsi cheese, which was 43.35% ± 1.50 for moisture, 20.24% ± 0.59 for protein, 24.70% ± 1.53 for fat, 11.52% ± 0.60 for ash, 9.96% ± 0.44 for salt, and pH 6.43 ± 0.16. However, cheeses prepared using 100% sheep’s and 100% cows’ milk, respectively showed the highest (26.85%) and lowest (14.77%) yields. Desalting and milk type had the highest effects on cheese texture and color, respectively. Considering all tested parameters, mixing equal proportions of sheep’s and cows’ milk ensures that the Nabulsi cheese produced is similar to that produced from 100% sheep’s milk, albeit with increased cohesiveness (0.52 ± 0.07for cheese made from sheep’s milk and 0.59 ± 0.05 for 1:1 sheep’s: cows’ milk mixture).
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Masek, Anna, and Malgorzata Latos-Brozio. "The Effect of Substances of Plant Origin on the Thermal and Thermo-Oxidative Ageing of Aliphatic Polyesters (PLA, PHA)." Polymers 10, no. 11 (2018): 1252. http://dx.doi.org/10.3390/polym10111252.
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The stabilization efficiency of flavonoids (rutin and hesperidin) in polyester (polylactide (PLA) and polyhydroxyalkaonate (PHA)) composites under oxygen at high temperature was investigated. The polymer was homogenized with three antioxidants then processed by extrusion. The effects of stabilizers on the following physicochemical properties were investigated: melt flow, Vicat softening temperature, surface energy, and color change (Cie-Lab space). The aim of this study was to improve the stability of aliphatic polyesters by extending and controlling their lifetime. Differential Scanning Calorimetry DSC and Thermogravimetric analysis DTG methods were used to confirm the stabilizing effects (the inhibition of oxidation) of flavonoids (rutin and hesperidin) on the ageing process of biodegradable polymers. The levels of migration of plant antioxidants from PLA and PHA were determined and compared to the industrial stabilizer (Chimassorb 944 UV absorber). Based on this study, a comparable-to-higher efficiency of the proposed flavonoids for the stabilization of polyesters was found when compared to the commercial stabilizers. Thus, in the future, natural plant-derived substances may replace toxic hindered amines, which are commonly used as light stabilizers (HALS—Hindered Amine Light Stabilizers) in the polymer industry.
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Pérez-Estébanez, M., R. Pastrana-Fábregas, J. Isasi-Marín, and R. Sáez-Puche. "Inorganic pigments based on fluorite-type oxynitrides." Journal of Materials Research 21, no. 6 (2006): 1427–33. http://dx.doi.org/10.1557/jmr.2006.0177.
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Zirconia oxynitride rare-earth-doped pigments were prepared by ammonolysis of the zirconium rare-earth oxides, previously synthesized using the citrate complexation/calcination route. Different coloration has been obtained, the intensity of which is a function of the nitrogen amount in the case of the oxynitrides; in the case of the oxides, both color and intensity depend on the doping amount of rare earth. The obtained phases, Zr(1−x)CexO2, Zr(1−x)RxO(2−x/2)□x/2, with R = Eu or Er and Zr(1−x)RxO(2−x/2−3/2y)Ny□x/2■y/2 (R = Ce, Eu, and Er), have been characterized by x-ray powder diffraction, scanning electron microscopy, and reflectance spectra data. These results show that the phases with minor rare-earth concentration adopt a baddeleyite-type structure, with a monoclinic symmetry, space group P21/c. By increasing the rare-earth doping, the obtained phases crystallize with the fluorite structure with tetragonal (P42/nmc) or cubic symmetry (Fm¯3m). On the other hand, the study of the magnetic properties of the oxides and oxynitrides indicate a paramagnetic behavior, and in the case of the cerium oxide, the nitridation process produces the reduction from Ce4+ to Ce3+. Diffuse reflectance data and CIE-LAB color coordinates suggest that these ceramics based on nitrogen containing zirconia are expected to be promising candidates as new ecological inorganic pigments.
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Koyama, Kento, Marin Tanaka, Byeong-Hyo Cho, Yusaku Yoshikawa, and Shige Koseki. "Predicting sensory evaluation of spinach freshness using machine learning model and digital images." PLOS ONE 16, no. 3 (2021): e0248769. http://dx.doi.org/10.1371/journal.pone.0248769.
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The visual perception of freshness is an important factor considered by consumers in the purchase of fruits and vegetables. However, panel testing when evaluating food products is time consuming and expensive. Herein, the ability of an image processing-based, nondestructive technique to classify spinach freshness was evaluated. Images of spinach leaves were taken using a smartphone camera after different storage periods. Twelve sensory panels ranked spinach freshness into one of four levels using these images. The rounded value of the average from all twelve panel evaluations was set as the true label. The spinach image was removed from the background, and then converted into a gray scale and CIE-Lab color space (L*a*b*) and Hue, Saturation and Value (HSV). The mean value, minimum value, and standard deviation of each component of color in spinach leaf were extracted as color features. Local features were extracted using the bag-of-words of key points from Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features). The feature combinations selected from the spinach images were used to train machine learning models to recognize freshness levels. Correlation analysis between the extracted features and the sensory evaluation score showed a positive correlation (0.5 < r < 0.6) for four color features, and a negative correlation (‒0.6 < r < ‒0.5) for six clusters in the local features. The support vector machine classifier and artificial neural network algorithm successfully classified spinach samples with overall accuracy 70% in four-class, 77% in three-class and 84% in two-class, which was similar to that of the individual panel evaluations. Our findings indicate that a model using support vector machine classifiers and artificial neural networks has the potential to replace freshness evaluations currently performed by non-trained panels.
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Bou-Belda, Eva, Daniel López-Rodríguez, Bàrbara Micó-Vicent, and Marilés Bonet-Aracil. "Direct and Reactive Dyes Recovery in Textile Wastewater Using Calcinated Hydrotalcite." Materials Science Forum 1063 (June 10, 2022): 233–42. http://dx.doi.org/10.4028/p-31v71q.
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Growing environmental conservation concerns have led researchers to seek the means to treat and recover wastewater. The textile industry dumps vast quantities of wastewater from textile dyes. By means of clays, dye waste can be separated and reused for other industrial processes. Clay absorption varies depending on the type of dye employed because factors like the reactivity of the dye molecule and its size are very important during the absorption process. The absorption capacity of calcined hydrotalcite at several concentrations was compared in a 0.05 g • L-1 solution of four distinct dyes: Direct Blue 199, Direct Red 23, Direct Blue 71 and Reactive Yellow. Dyes have different molecular weights because the weight of reactive dyes is considerably lighter than that of direct dyes, which is why the Lambert-Beer lines of each dye are previously considered. We worked with a 5 g • L-1 clay concentration to introduce the dye into the clay by stirring for 24 h in 100 ml of each dye solution before filtering it and leaving it to dry. In all cases, the dye absorption by nanoclay was nearly absolute and the initial solution was very clean, which are excellent results from the wastewater treatment point of view. Color measurement was performed by a Jasco V-670, double-beam spectrophotometre between 190-2700 nm. Differences in color were calculated and represented in CIE-Lab* color space diagrams. Finally, thermogravimetric (TGA) and X-ray diffraction (XRD) analyses were carried out to ensure both nanoclay-dye interactions and hydrotalcite structure recovery. No large differences were observed under these conditions, which reinforces the idea of using low nanoclay concentrations.
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Dhaterwal, D., M. Matoria, A. Dalal, Surender Kumar, and Sonika Singh. "Synthesis and Structural Features of Tunable Emitting Single- Phased Eu3+/ Tb3+ Co- Doped LaAlO3 Nanophosphors." Журнал структурной химии 65, no. 8 (2024): 130877. http://dx.doi.org/10.26902/jsc_id130877.
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In the prevailing study, single- phased color- tunable La1-x-yEuxTbyAlO3 co- doped nanocrystalline phosphors have been synthesized via the most simplistic and low cost urea- aided solution combustion synthetic route. This was done by adjusting the doping concentration of Eu3+ (x = 0.01, 0.03, 0.05, 0.07 mol) and Tb3+ (y = 0.03 mol) ions in the LaAlO3 host lattice. The X- ray powder diffraction (XRD) and Rietveld refinement analysis confirmed the formation of single- phased La0.97-xAlO3: xEu3+/ 0.03Tb3+ (x = 0.07), co- doped nanophosphor at 800°C. The synthesized nanophosphors were crystallized in cubic crystal system having Pm3̄m space group with 221 space group number. The morphological studies i.e., field emission scanning electron microscopy (FE- SEM), and transmission electron microscope (TEM) images depicted the agglomerated clusters of distinct spherical shaped particles of La0.97-xAlO3: xEu3+/ 0.03Tb3+ in nano- regime. Energy dispersive X- ray analysis (EDAX) was employed to ascertain the real elemental mapping of the fabricated phosphors. Through diffuse reflectance (DR) spectroscopy measurements, the optical band gap value for La0.92Eu0.05Tb0.03AlO3 nanocrystalline phosphor was determined to be 5.26 eV. The photoluminescent excitation (PLE) and photoluminescent emission (PL) spectra were studied in detail as a function of Eu3+ ion contents and La1-x-0.03AlO3: xEu3+/ 0.03Tb3+ (x = 0.05 mol) co- doped sample exhibits strongest emission and over the 0.05 Eu3+ ions doping concentration, the emission intensity falls as a consequence of the quenching phenomenon. The concentration quenching in directed co- doped nanophosphors was attributed to the dipole - dipole interactions. With the exploitation of photoluminescent data, Commission International de I'Eclairage 1931 (CIE) color coordinates (x, y) of co- doped samples have been calculated from the emission spectra, which revealed the color could be tuned i.e., from orange to red region in La0.97-xAlO3: xEu3+/ 0.03Tb3+ samples with divergences in the Eu3+ and other significant photometric assets viz. correlated color temperature (CCT), color purity (CP) of the synthesized La1-x-yAlO3: xEu3+, yTb3+ co- doped nanocrystalline photoluminescent materials were also determined. The studies outcomes suggested that Eu3+/ Tb3+ co- doped LaAlO3 phosphors have great potential as color- tunable luminescent material in solid- state lighting and display technologies.
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Endah, Sukmawati Nur, Retno Kusumaningrum, and Helmie Arif Wibawa. "Color Space to Detect Skin Image: The Procedure and Implication." Scientific Journal of Informatics 4, no. 2 (2017): 143–49. http://dx.doi.org/10.15294/sji.v4i2.12013.
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Skin detection is one of the processes to detect the presence of pornographic elements in an image. The most suitable feature for skin detection is the color feature. To be able to represent the skin color properly, it is needed to be processed in the appropriate color space. This study examines some color spaces to determine the most appropriate color space in detecting skin color. The color spaces in this case are RGB, HSV, HSL, YIQ, YUV, YCbCr, YPbPr, YDbDr, CIE XYZ, CIE L*a*b*, CIE L*u* v*, and CIE L*ch. Based on the test results using 400 image data consisting of 200 skin images and 200 non-skin images, it is obtained that the most appropriate color space to detect the color is CIE L*u*v*.
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Rasid Mamat, Abd, Fatma Susilawati Mohamed, Mohamad Afendee Mohamed, Norkhairani Mohd Rawi, and Mohd Isa Awang. "Silhouette index for determining optimal k-means clustering on images in different color models." International Journal of Engineering & Technology 7, no. 2.14 (2018): 105. http://dx.doi.org/10.14419/ijet.v7i2.14.11464.
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Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.
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Sun, Bangyong, Han Liu, Shisheng Zhou, and Wenli Li. "Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/418651.
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The polynomial regression method is employed to calculate the relationship of device color space and CIE color space for color characterization, and the performance of different expressions with specific parameters is evaluated. Firstly, the polynomial equation for color conversion is established and the computation of polynomial coefficients is analysed. And then different forms of polynomial equations are used to calculate the RGB and CMYK’s CIE color values, while the corresponding color errors are compared. At last, an optimal polynomial expression is obtained by analysing several related parameters during color conversion, including polynomial numbers, the degree of polynomial terms, the selection of CIE visual spaces, and the linearization.
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Sukram, Sukram, and Sutikno Sutikno. "Pengaruh Suhu Dan Waktu Tinggal Terhadap Kecenderungan Menguning Pada Proses Produksi Alumunium Fasad." JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri 2, no. 1 (2019): 64. http://dx.doi.org/10.30737/jatiunik.v2i2.330.
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Painting using paint powder is one of the techniques of protection against corrosion are evolving rapidly. Powder paints have aesthetic value approaching liquid paint as well as durability and relative utilization is better than liquid paint. The process of maturation of the paint powder that is only done with the process of warming at a certain temperature and a certain span of time. Standard maturation process known as maturation curve (curing folder). The difference in temperature and time against standard value ranges of risk occurrence of color change especially in white color (light). Therefore, do the research to find out the influence of temperature and time of warming up against the tendency of yellowing in white powder paint. Colour measurement is performed using a colorimeter in units of CIE Lab. Value b in CIE lab color trend show the yellowish or bluish. Temperature and time of warming up is the variable factor research determined 5.Keyword : paint powder, maturation, temperature, color. Pengecatan menggunakan cat bubuk merupakan salah satu teknik perlindungan terhadap korosi yang berkembang secara pesat. Cat bubuk memiliki nilai estetika mendekati cat cair serta daya tahan dan utilisasi yang relative lebih baik dibanding cat cair. Proses pematangan cat bubuk yang hanya dilakukan dengan proses pemanasan pada suhu tertentu dan rentang waktu tertentu. Standard proses pematangan dikenal dengan kurva pematangan (curing map). Perbedaan suhu dan waktu terhadap rentang nilai standard menimbulkan resiko terjadinya perubahan warna khususnya pada warna putih (terang). Oleh sebab itu dilakukan penelitian untuk mengetahui pengaruh suhu dan waktu pemanasan terhadap kecenderungan menguning pada cat bubuk warna putih. Pengukuran warna dilakukan dengan menggunakan colorimeter dalam satuan CIE Lab. Nilai b pada CIE lab menunjukan kecenderungan warna kekuningan atau kebiruan. Suhu dan waktu pemanasan merupakan variabel penelitian yang faktornya ditentukan 5⁰C dan 5 menit diluar kurva pematangan. Kata kunci: cat bubuk, pematangan, suhu, warna.
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Zheng, Yuan Lin, Shi Sheng Zhou, Yong Hong Qi, and Lin Lin Zhang. "Performance of CIE LAB-Based Color Difference Formulae under Different Viewing Conditions." Advanced Materials Research 457-458 (January 2012): 1294–98. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.1294.
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In order to investigate the performance of color difference formulae under different viewing conditions 144 pairs of sample around 17 color centers were designed and printed, and then assessed visually under four different viewing condition. STRESS values between the visual color difference and calculated color difference by five CIELAB-based color difference formulae CIELAB, BFD, CMC, CIE94, CIEDE200 were calculated. The result shows that the formulae have the similar performance but CIE94 is the best in all viewing conditions and CIELAB and BFD are the worst. All the color difference formulae have the best performance under illuminant D65 with illuminance of 1000 lx and gray background