Relevant bibliographies by topics / RGB-based colour thresholding

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Academic literature on the topic 'RGB-based colour thresholding'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "RGB-based colour thresholding"

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Rathna Priya, T. S., and Annamalai Manickavasagan. "Evaluation of segmentation methods for RGB colour image-based detection of Fusarium infection in corn grains using support vector machine (SVM) and pre-trained convolution neural network (CNN)." Canadian Biosystems Engineering 64, no. 1 (2022): 7.09–7.20. http://dx.doi.org/10.7451/cbe.2022.64.7.9.

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This study evaluated six segmentation methods (clustering, flood-fill, graph-cut, colour-thresholding, watershed, and Otsu’s-thresholding) for segmentation accuracy and classification accuracy in discriminating Fusarium infected corn grains using RGB colour images. The segmentation accuracy was calculated using Jaccard similarity index and Dice coefficient in comparison with the gold standard (manual segmentation method). Flood-fill and graph-cut methods showed the highest segmentation accuracy of 77% and 87% for Jaccard and Dice evaluation metrics, respectively. Pre-trained convolution neural
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Rahmawati, Sri, GS Achmad Daengs, Teri Ade Putra, Abdi Rahim Damanik, and Anjar Wanto. "Brain Image Decomposition on Image Alteration." Journal of Physics: Conference Series 2394, no. 1 (2022): 012020. http://dx.doi.org/10.1088/1742-6596/2394/1/012020.

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Abstract Image transformation is essential to explore and find out specific information that does not exist and has not been previously known from an image, such as pixels, geometry, size or colour. Therefore, this paper aims to analyze the image transformation by generating the value of the thresholding method from low to high in image segmentation. The segmentation process works based on two-colour models, namely HSV and RGB colours. Image segmentation problems occur when an object has more than two colours. There is lighting that affects the condition of the thing, so it is proposed to chan
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Golding, Vaughn Peter, Zahra Gharineiat, Hafiz Suliman Munawar, and Fahim Ullah. "Crack Detection in Concrete Structures Using Deep Learning." Sustainability 14, no. 13 (2022): 8117. http://dx.doi.org/10.3390/su14138117.

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Infrastructure, such as buildings, bridges, pavement, etc., needs to be examined periodically to maintain its reliability and structural health. Visual signs of cracks and depressions indicate stress and wear and tear over time, leading to failure/collapse if these cracks are located at critical locations, such as in load-bearing joints. Manual inspection is carried out by experienced inspectors who require long inspection times and rely on their empirical and subjective knowledge. This lengthy process results in delays that further compromise the infrastructure’s structural integrity. To addr
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Samantaray, Leena, Sabonam Hembram, and Rutuparna Panda. "A New Harris Hawks-Cuckoo Search Optimizer for Multilevel Thresholding of Thermogram Images." Revue d'Intelligence Artificielle 34, no. 5 (2020): 541–51. http://dx.doi.org/10.18280/ria.340503.

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The exploitation capability of the Harris Hawks optimization (HHO) is limited. This problem is solved here by incorporating features of Cuckoo search (CS). This paper proposes a new algorithm called Harris hawks-cuckoo search (HHO-CS) algorithm. The algorithm is validated using 23 Benchmark functions. A statistical analysis is carried out. Convergence of the proposed algorithm is studied. Nonetheless, converting color breast thermogram images into grayscale for segmentation is not effective. To overcome the problem, we suggest an RGB colour component based multilevel thresholding method for br
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Gocławski, Jarosław, Joanna Sekulska-Nalewajko, and Elżbieta Kuźniak. "Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses." International Journal of Applied Mathematics and Computer Science 22, no. 3 (2012): 669–84. http://dx.doi.org/10.2478/v10006-012-0050-5.

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Abstract The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant’s reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to obtain a leaf blade mask. The second stage of the method consists in the classification of
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Karthiga.PL1, S.Md.Mansoor Roomi2 Kowsalya.J3. "TRAFFIC-SIGN RECOGNITION FOR AN INTELLIGENT VEHICLE/DRIVER ASSISTANT SYSTEM USING HOG." Computer Science & Engineering: An International Journal (CSEIJ), 6, no. 1 (2019): 15–23. https://doi.org/10.5281/zenodo.3446093.

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In order to be deployed in driving environments, Intelligent transport system (ITS) must be able to recognize and respond to exceptional road conditions such as traffic signs, highway work zones and imminent road works automatically. Recognition of traffic sign is playing a vital role in the intelligent transport system, it enhances traffic safety by providing drivers with safety and precaution information about road hazards. To recognize the traffic sign, the system has been proposed with three phases. They are Traffic board Detection, Feature extraction and Recognition. The detection phase c
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Skarlatos, D., and M. Vlachos. "VEGETATION REMOVAL FROM UAV DERIVED DSMS, USING COMBINATION OF RGB AND NIR IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2 (May 28, 2018): 255–62. http://dx.doi.org/10.5194/isprs-annals-iv-2-255-2018.

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Current advancements on photogrammetric software along with affordability and wide spreading of Unmanned Aerial Vehicles (UAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance and applications of large format aerial overlaps cameras and photographs in Digital Surface Model (DSM) production and LIDAR data is well documented in literature, this is not the case for UAV photography. Additionally, the main disadvantage of photogrammetry is the inability to map the dead ground (terrain), when we deal with areas that include vegeta
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Sharun, Khan, S. Amitha Banu, Merlin Mamachan, et al. "Comparative Evaluation of Masson's Trichrome and Picrosirius Red Staining for Digital Collagen Quantification Using ImageJ in Rabbit Wound Healing Research." Journal of Experimental Biology and Agricultural Sciences 11, no. 5 (2023): 822–33. http://dx.doi.org/10.18006/2023.11(5).822.833.

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The therapeutic potential of Pluronic F127 (PF127) hydrogel loaded with adipose-derived stromal vascular fraction (AdSVF), mesenchymal stem cells (AdMSC), and conditioned media (AdMSC-CM) for repairing full-thickness skin wounds was evaluated using a rabbit model. The rabbits were randomly divided into eight groups with six animals each and treatment was given as per the predetermined protocol (3 doses at one-week interval): Group A (Control), Group B (AdSVF), Group C (AdMSC), Group D (AdMSC-CM), Group E (PF127), Group F (AdSVF + PF127), Group G (AdMSC + PF127), and Group H (AdMSC-CM + PF127).
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Caunce, S., D. Dadarwal, G. Adams, P. Brar, and J. Singh. "121 THREE-DIMENSIONAL ASSESSMENT OF EARLY CORPUS LUTEUM VASCULARITY IN BUFFALO (BUBALUS BUBALIS)." Reproduction, Fertility and Development 29, no. 1 (2017): 169. http://dx.doi.org/10.1071/rdv29n1ab121.

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The aim of the study was to develop an objective method to assess the vascular flow to the early corpus luteum (CL) in buffaloes using colour Doppler ultrasound data. Our hypothesis was that 3-dimensional (3D) volumetric analysis of vascularity would demonstrate lower variability between animals compared with conventional 2-dimensional (2D) analysis of single images. Wave emergence and ovulation was synchronized in buffalo (n = 16) using prostaglandin-GnRH based protocols. Colour Doppler ultrasonography (MyLab5, 7.5-MHz linear array, colour gain 65%) was performed daily from Day −2 to 4 (Day 0
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Altukhov, V. G. "Plant leaf images computerized segmenation." IOP Conference Series: Earth and Environmental Science 957, no. 1 (2022): 012002. http://dx.doi.org/10.1088/1755-1315/957/1/012002.

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Abstract In this paper the comparison of RGB, HSV and CIELab color spaces is considered in view of diseased leaf images segmentation by color thresholding method. In such tasks HSV and CIELab outperform RGB. Thresholding method based upon HSV or CIELab color spaces can be applied to measuring leaves total area, diseased and healthy surfaces area, as well as dataset composing in machine learning.
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Conference papers on the topic "RGB-based colour thresholding"

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Tominaga, Shoji. "Segmentation method for natural color images." In OSA Annual Meeting. Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.mm2.

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Image segmentation for partitioning an image into a set of meaningful regions is a key step in color image analysis. One basic technique is a histogram thresholding method using 3-D color features of RGB signals. However, the performance of segmentation depends not only on its algorithm but also on the color features. We have developed a useful segmentation method by means of the three perceptual attributes of hue, lightness, and saturation. The algorithm is based on a recursive thresholding of the histograms. The Munsell color system is used as the perceptually uniform color space. We use dir
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Abrol, Vipasha, Sabrina Dhalla, Jasleen Saini, Ajay Mittal, Sukhwinder Singh, and Savita Gupta. "Automated Segmentation of Leukocytes using Marker-based Watershed Algorithm from Blood Smear Images." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.9.

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The aim of this paper is to perform segmentation of white blood cells (WBCs) using blood smear images with the help of image processing techniques. Traditionally, the process of morphological analysis of cells is performed by a medical expert. This process is quite tedious and time consuming. The equipments used to perform the experiments are very costly and might not be available in all hospitals. Further, the whole process is quite lengthy and prone to error easily because of the lack of standard set of procedure. Hence there is a need for innovative and efficient techniques. An automated im
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Schraml, Dominik, Konstantin Trambickii, and Gunther Notni. "PixLabelCV - Labeling images for semantic segmentation fast, pixel-precise and offline." In Computer Science Research Notes. University of West Bohemia, Czech Republic, 2024. http://dx.doi.org/10.24132/csrn.3401.6.

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Image annotation, also called labeling is a necessary task for any supervised learning approach to obtain ground truth data for model training. This article offers a comprehensive survey of contemporary image annotation tools,grouping freely accessible ones based on their service range, speed, and data privacy assurances. In our exploration for tools capable of executing pixel-precise semantic labeling, we identified a shortage of swift, free image annotation tools that don’t require users to upload their data to third-party servers. Therefore, we introduce "PixLabelCV" - a lightweight, fast,
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