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Thematische Bibliographien / Color SIFT / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Color SIFT“

Autor: Grafiati

Veröffentlicht am 3. Juni 2025

Zuletzt aktualisiert am 31. Juli 2025

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1

Zhang, Jie Yu, Hai Yong Wu, Shu Chen, and De Shen Xia. "The Target Tracking Method Based on Camshift Algorithm Combined with SIFT." Advanced Materials Research 186 (January 2011): 281–86. http://dx.doi.org/10.4028/www.scientific.net/amr.186.281.

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Since Camshift algorithm leads to failed tracking results when the color information of the target region is similar with the background or is not precise enough, to solve this problem a tracking method based on Camshift and SIFT was proposed in this paper. In this method, SIFT feature points, which were used to construct the color histogram and the color probability distribution, were extracted from the target region first. Then SIFT points were also extracted from the search region and these two sets of SIFT points were matched. Since the proposed method used the matched SIFT points to prope

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Trujillo-Romero, Felipe, Santiago Omar Caballero Morales, Karen-Lizbeth Flores-Rodriguez, Carlos Garcia-Capulin, and Raúl Sanchez-Yanez. "A Reduced Spherical Model for Optimization of Image Recognition through 3D Color Histograms." International Journal of Combinatorial Optimization Problems and Informatics 13, no. 3 (2022): 43–55. https://doi.org/10.61467/2007.1558.2022.v13i3.308.

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A 3D color histogram is an image processing technique used to visualize the distribution of colors (Red-Blue-Green) in a picture. Because color distribution does not significantly change if a pictured object is translated or rotated, a 3D color histogram can be used as descriptor for automatic object recognition. However, this task requires cubes with high dimensionality. Within this context, the present work contributes with an approach to reduce the high dimensionality of the 3D color histogram and improve it as descriptor for object recognition. Tests performed with three databases (COIL-10

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HAN, Yechen, and HIRAI Shinichi. "2A1-J03 Color Filter in SIFT Matching(Robot Vision (1))." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2013 (2013): _2A1—J03_1—_2A1—J03_4. http://dx.doi.org/10.1299/jsmermd.2013._2a1-j03_1.

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Yuan, Wenan, Sai Raghavendra Prasad Poosa, and Rutger Francisco Dirks. "Comparative Analysis of Color Space and Channel, Detector, and Descriptor for Feature-Based Image Registration." Journal of Imaging 10, no. 5 (2024): 105. http://dx.doi.org/10.3390/jimaging10050105.

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The current study aimed to quantify the value of color spaces and channels as a potential superior replacement for standard grayscale images, as well as the relative performance of open-source detectors and descriptors for general feature-based image registration purposes, based on a large benchmark dataset. The public dataset UDIS-D, with 1106 diverse image pairs, was selected. In total, 21 color spaces or channels including RGB, XYZ, Y′CrCb, HLS, L*a*b* and their corresponding channels in addition to grayscale, nine feature detectors including AKAZE, BRISK, CSE, FAST, HL, KAZE, ORB, SIFT, an

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Zhang, Jun, Lin Zhang, An Quan Sun, Shu Bing Li, Xiao Bing Tang, and Hong Wang. "SIFT Feature Extraction Based on Color Energy Region." Applied Mechanics and Materials 411-414 (September 2013): 1201–4. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1201.

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In content-based image feature extraction research areas, SIFT feature occupies a very important position. In 2004 it was first proposed, widely used in object recognition, video tracking, scene recognition, image retrieval and other issues, and achieved great success. But the extraction of image SIFT features needs a huge amount of computation. This paper presents the concept of color energy in where it has great information, and extract large color energy regions, extracted SIFT feature points in them. Although losing some of the feature points, this method effectively reduces the computatio

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Liu, Ming Hua, Chuan Sheng Wang, and Xian Lun Wang. "Particle Filter Target Tracking Algorithm Based on the SIFT and Color Features Fusion." Applied Mechanics and Materials 734 (February 2015): 476–81. http://dx.doi.org/10.4028/www.scientific.net/amm.734.476.

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Aiming at the poor robustness problem of using single feature in the target tracking process, a novel tracking algorithm based on color and SIFT features fusion in particle filter framework is presented in complex environments. Color and SIFT features are selected to establish the target model according to their stability, The scale and rotation invariance of SIFT feature and resistance occlusion property of color feature has been fused in the particle filter framework adaptively. According to the dynamic change of the tracking scene, the fusion weights is updated adaptively. Experimental resu

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Zhang, Xiaoli, Punan Li, and Yibing Li. "Feature Point Extraction and Motion Tracking of Cardiac Color Ultrasound under Improved Lucas–Kanade Algorithm." Journal of Healthcare Engineering 2021 (August 3, 2021): 1–10. http://dx.doi.org/10.1155/2021/4959727.

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The purpose of this research is to study the application effect of Lucas–Kanade algorithm in right ventricular color Doppler ultrasound feature point extraction and motion tracking under the condition of scale invariant feature transform (SIFT). This study took the right ventricle as an example to analyze the extraction effect and calculation rate of SIFT algorithm and improved Lucas–Kanade algorithm. It was found that the calculation time before and after noise removal by the SIFT algorithm was 0.49 s and 0.46 s, respectively, and the number of extracted feature points was 703 and 698, respec

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Abu Doush, Iyad, and Sahar AL-Btoush. "Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms." Journal of King Saud University - Computer and Information Sciences 29, no. 4 (2017): 484–92. http://dx.doi.org/10.1016/j.jksuci.2016.06.003.

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9

Kang, Nan Nan, Xiao Fang Wang, and Rong Rong Zhang. "Image Classification Based on Color Topic Model." Applied Mechanics and Materials 556-562 (May 2014): 4770–73. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4770.

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This paper addresses semantic image classification with topic model, which focusing on discovering a hidden semantic to solve the semantic gap between low-level visual feature and high-level feature. In our approach, Latent Dirichlet Allocation (LDA) model successfully reflect the high level features and the RGB SIFT features which integrating the Scale-invariant feature transform (SIFT) features with color features on the assumption that pictures generated by mixture of latent semantic which we called topics. The proposed approach has a sufficient theoretical basis and the experimental evalua

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Nosovskiy, Gleb. "Geometrical coding of color images." Publications de l'Institut Math?matique (Belgrade) 103, no. 117 (2018): 159–73. http://dx.doi.org/10.2298/pim1817159n.

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Formal analysis and computer recognition of 2D color images is important branch of modern computer geometry. However, existing algorithms, although they are highly developed, are not quite satisfactory and seem to be much worse than (unknown) algorithms, which our brain uses to analyze eye information. Almost all existing algorithms omit colors and deal with grayscale transformations only. But in many cases color information is important. In this paper fundamentally new method of coding and analyzing color digital images is suggested. The main point of this method is that a full-color digital

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Efendi, Muhamad Masjun, Salman Salman, and Moh Subli. "Analysis Manipulation Copy-Move on Image Digital using SIFT Method and Histogram Color RGB." JISA(Jurnal Informatika dan Sains) 5, no. 2 (2022): 120–23. http://dx.doi.org/10.31326/jisa.v5i2.1334.

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The application of the SIFT (Scale Invariant feature transform) algorithm and the RGB color histogram in Matlab can detect the suitability of objects in digital images and perform tests accurately. In this study, we discuss the implementation to obtain object compatibility on digital images that have been manipulated using the SIFT Algorithm method on the Matlab source, namely by comparing the original image with the manipulated image. The suitability of objects in digital images is obtained from the large number of keypoints obtained, other additional parameters, namely comparing the number o

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Wang, Sen, Xiaoming Sun, Pengfei Liu, Kaige Xu, Weifeng Zhang, and Chenxu Wu. "Research on Remote Sensing Image Matching with Special Texture Background." Symmetry 13, no. 8 (2021): 1380. http://dx.doi.org/10.3390/sym13081380.

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The purpose of image registration is to find the symmetry between the reference image and the image to be registered. In order to improve the registration effect of unmanned aerial vehicle (UAV) remote sensing imagery with a special texture background, this paper proposes an improved scale-invariant feature transform (SIFT) algorithm by combining image color and exposure information based on adaptive quantization strategy (AQCE-SIFT). By using the color and exposure information of the image, this method can enhance the contrast between the textures of the image with a special texture backgroun

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WANG Rui, 王睿, and 朱正丹 ZHU Zheng-dan. "SIFT matching with color invariant characteristics and global context." Optics and Precision Engineering 23, no. 1 (2015): 295–301. http://dx.doi.org/10.3788/ope.20152301.0295.

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Lacheheb, Hadjer, and Saliha Aouat. "SIMIR: New mean SIFT color multi-clustering image retrieval." Multimedia Tools and Applications 76, no. 5 (2016): 6333–54. http://dx.doi.org/10.1007/s11042-015-3167-3.

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Zeng, Huanqiang, Kai-Kuang Ma, Chen Wang, and Canhui Cai. "SIFT-flow-based color correction for multi-view video." Signal Processing: Image Communication 36 (August 2015): 53–62. http://dx.doi.org/10.1016/j.image.2015.05.008.

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Cang, Gui Hua, and Jian Ping Yue. "Registration of Building Intensity Image and its Color Image Using SIFT Algorithm." Applied Mechanics and Materials 638-640 (September 2014): 2160–63. http://dx.doi.org/10.4028/www.scientific.net/amm.638-640.2160.

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Fusion of close range photogrammetry (CRP) and terrestrial laser scanning (TLS) technology has been a hot topic in the field of building reconstruction. There are many ways to realize the fusion of the two kind data. In this paper, we propose a method for 3D-2D data registration based on Scale Invariant Feature Transform (SIFT) algorithm and range intensity data. 3D terrestrial laser scanner and digital camera are different sensors, which will lead to large difference between intensity image (derived from range intensity data) and color image. The traditional image matching method can not appl

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Oğuz, Oğuzhan, A. Çetin, and Rengul Atalay. "Classification of Hematoxylin and Eosin Images Using Local Binary Patterns and 1-D SIFT Algorithm." Proceedings 2, no. 2 (2018): 94. http://dx.doi.org/10.3390/proceedings2020094.

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In this paper, Hematoxylin and Eosin (H&E) stained liver images are classified by using both Local Binary Patterns (LBP) and one dimensional SIFT (1-D SIFT) algorithm. In order to obtain more meaningful features from the LBP histogram, a new feature vector extraction process is implemented for 1-D SIFT algorithm. LBP histograms are extracted with different approaches and concatenated with color histograms of the images. It is experimentally shown that,with the proposed approach, it possible to classify the H&E stained liver images with the accuracy of 88 % .

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Macêdo, Samuel, Givânio Melo, and Judith Kelner. "A comparative study of grayscale conversion techniques applied to SIFT descriptors." Journal on Interactive Systems 6, no. 2 (2015): 1. http://dx.doi.org/10.5753/jis.2015.662.

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In computer vision, gradient-based tracking is usually performed from monochromatic inputs. However, a few research studies consider the influence of the chosen color-tograyscale conversion technique. This paper evaluates the impact of these conversion algorithms on tracking and homography calculation results, both being fundamental steps of augmented reality applications. Eighteen color-to-greyscale algorithms were investigated. These observations allowed the authors to conclude that the methods can cause significant discrepancies in the overall performance. As a related finding, experiments

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AI, Dan-ni, Xian-hua HAN, Xiang RUAN, and Yen-wei CHEN. "Color Independent Components Based SIFT Descriptors for Object/Scene Classification." IEICE Transactions on Information and Systems E93-D, no. 9 (2010): 2577–86. http://dx.doi.org/10.1587/transinf.e93.d.2577.

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Li, Yuanman, Jiantao Zhou, and An Cheng. "SIFT Keypoint Removal via Directed Graph Construction for Color Images." IEEE Transactions on Information Forensics and Security 12, no. 12 (2017): 2971–85. http://dx.doi.org/10.1109/tifs.2017.2730362.

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Damarsiwi, Dyah Kartika, Elindra Ambar Pambudi, Maulida Ayu Fitriani, and Feri Wibowo. "Face Detection in Complex Background using Scale Invariant Feature Transform and Haar Cascade Classifier Methods." Sinkron 8, no. 2 (2024): 852–60. http://dx.doi.org/10.33395/sinkron.v8i2.13556.

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Face detection is a process by a computer system that can find and identify human faces in digital images or videos. One of the main challenges faced in the face detection process is the complex background. Complex backgrounds, such as many color combinations in the image, can interfere with the detection process. To overcome this challenge, this research uses a combination of two methods: Scale Invariant Feature Transform (SIFT) and Haar Cascade Classifier. Scale Invariant Feature Transform (SIFT) is a method used in image processing to identify and describe unique features in an image. The S

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Al Caruban, Rosidin, Bambang Sugiantoro, and Yudi Prayudi. "ANALISIS PENDETEKSI KECOCOKAN OBJEK PADA CITRA DIGITAL DENGAN METODE ALGORITMA SIFT DAN HISTOGRAM COLOR RGB." Cyber Security dan Forensik Digital 1, no. 1 (2018): 20–27. http://dx.doi.org/10.14421/csecurity.2018.1.1.1235.

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Through using tools of image processing on digital images just like gimp and adobe photoshop applications, an image on digital images can be a source of information for anyone who observes it. On one hand, those applications can easily change or manipulate the authenticity of the image. On the other hand, they can be misused to undermine the credibility of the authenticity of the image in various aspects. Thus, they can be considered as a crime. The implementation of the SIFT Algorithm (Scale Invariant feature transform) and RGB color histogram in Matlab can detect object fitness in digital im

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Ghindawi, Ikhlas Watan, and Lamyaa Mohammed Kadhim. "Development of Adaptive Tracking using Advance Filter and Selection Features Method." International Journal of Engineering Research and Advanced Technology 08, no. 09 (2022): 01–10. http://dx.doi.org/10.31695/ijerat.2022.8.10.1.

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Recently, Kalman filter(KF)-based algorithms of tracking had demonstrated to be effective, however, their efficiency is limited by fixed feature selections and the possibility of model drift. In the presented research, we offer a new adaptive feature selection-based tracking approach that maintains the KF’s excellent discriminating power. Depending on scores of confidence regarding features in every one of frames, the suggested approach might select (automatically)either SIFT feature or the colour feature for the tracking. With a use of KF, a response map related to the SIFT features and color

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Chen, Jiann-Liang, Yi-Wei Ma, and Kuan-Lung Huang. "Intelligent Visual Similarity-Based Phishing Websites Detection." Symmetry 12, no. 10 (2020): 1681. http://dx.doi.org/10.3390/sym12101681.

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This work proposes an intelligent visual technique for detecting phishing websites. The phishing websites are classified into three categories: very similar, local similar, and non-imitating. For cases of ‘very similar’, this study uses the wavelet Hashing (wHash) mechanism with a color histogram to evaluate the similarity. In cases of ‘local similarity’, this study uses the Scale-Invariant Feature Transform (SIFT) technique to evaluate the similarity. This work concerns ‘very similar’ and ‘local similar’ cases to detect phishing websites. The results of the experiments reveal that the wHash m

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SHAH, JAMAL HUSSAIN, ZONGHAI CHEN, MUHAMMAD SHARIF, MUSSARAT YASMIN, and STEVEN LAWRENCE FERNANDES. "A NOVEL BIOMECHANICS-BASED APPROACH FOR PERSON RE-IDENTIFICATION BY GENERATING DENSE COLOR SIFT SALIENCE FEATURES." Journal of Mechanics in Medicine and Biology 17, no. 07 (2017): 1740011. http://dx.doi.org/10.1142/s0219519417400115.

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Currently, identifying humans using biomechanics-based approaches has gained a lot of significance for person re-identification. Biomechanics-based approaches use knee-hip angle–angle relationships and body movements for person re-identification. Generally, biomechanics of human walking and running is used for person re-identification. In fact, person re-identification is a complex and important task in academia as well as industry and remains an unsolved issue in the computer vision field. The subjects most commonly addressed regarding person re-identification include significant feature extr

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Manthale, Priyanka, та Geeta Patil. "Exposing Digital Image Forgeries by Illumination Color Classiﬁcation using Sift Algorithm". International Journal of Computer Applications 177, № 1 (2017): 9–13. http://dx.doi.org/10.5120/ijca2017915436.

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Li, Yibo, Xuezheng Zhuang, and Yanmei Liu. "UPF Tracking Method Based on Color and SIFT Features Adaptive Fusion." International Journal of Signal Processing, Image Processing and Pattern Recognition 7, no. 6 (2014): 379–90. http://dx.doi.org/10.14257/ijsip.2014.7.6.33.

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Zhao, Yan, Yuwei Zhai, Eric Dubois, and Shigang Wang. "Image matching algorithm based on SIFT using color and exposure information." Journal of Systems Engineering and Electronics 27, no. 3 (2016): 691–99. http://dx.doi.org/10.1109/jsee.2016.00072.

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KHAZAB, MOHAMMAD, DAN-NI AI, JEFFREY TWEEDALE, YEN-WEI CHEN, and LAKHMI JAIN. "AN AGENT-ORIENTED APPROACH FOR IMAGE CLASSIFICATION WITH ICA-COLOR SIFT." International Journal on Artificial Intelligence Tools 21, no. 02 (2012): 1240003. http://dx.doi.org/10.1142/s0218213012400039.

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This paper discusses the research conducted on developing a Multi-Agent System (MAS) for solving an image classification task. The aim of this research is to equip agents in MAS with reusable autonomous capabilities. The system provides a flexible framework for developing the communication aspects within an agent-oriented architecture to program agents that dynamically acquire functionality at runtime using event based messaging. In this research agents are equipped with unique image processing capabilities and required to interact and cooperate to achieve the goal. Complementary research on a

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Ma, Jing, Yuan Li, and Qing Lin Wang. "Target Recognition and Features ExtractionBased on ROI and SIFT Descriptors." Applied Mechanics and Materials 220-223 (November 2012): 1153–57. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1153.

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This paper presents a target recognition method based on SIFT features matching and image ROI technology for vision system of assembly robots. In order to accelerate target recognition method, color histogram is used to detect the region of interest in images, then SIFT algorithm is employed in the ROI to extract the features. Thereby, the image Gaussian pyramid structure is simplified and the computation cost is reduced significantly. The experimental results show that this method can quickly recognize the objects without the loss of robustness and accuracy, and can provide necessary visual f

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Boonsivanon, Krittachai, and Worawat Sa-Ngiamvibool. "A SIFT Description Approach for Non-Uniform Illumination and Other Invariants." Ingénierie des systèmes d information 26, no. 6 (2021): 533–39. http://dx.doi.org/10.18280/isi.260603.

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The new improvement keypoint description technique of image-based recognition for rotation, viewpoint and non-uniform illumination situations is presented. The technique is relatively simple based on two procedures, i.e., the keypoint detection and the keypoint description procedure. The keypoint detection procedure is based on the SIFT approach, Top-Hat filtering, morphological operations and average filtering approach. Where this keypoint detection procedure can segment the targets from uneven illumination particle images. While the keypoint description procedures are described and implement

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Lv, Feng, Chunmei ZHANG та Changwei Lv. "Image recognition of individual cow based on SIFT in Lαβ color space". MATEC Web of Conferences 176 (2018): 01023. http://dx.doi.org/10.1051/matecconf/201817601023.

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Using image recognition technology to identify individual dairy cattle with her biological features shows strong stability. This kind of non-contact, high precision and low cost individual recognition methods based on image processing are more and more popular recently to replace the electronic tag and ear mark which can hurt the cattle’s psychology and physical health and can affect cattle’s behavior. By comparing the various color space transformations, he proposed a scale-invariant feature transform algorithm based on the Luminace of Lαβ color space. With this algorithm, a biological featur

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Cormier, Laurent, and Cécile Noirot. "Understanding the Influence of Copper on the Color of Glasses and Glazes: Copper Environment and Redox." Glass Europe 2 (August 23, 2024): 55–82. http://dx.doi.org/10.52825/glass-europe.v2i.1274.

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This study explores the influence of copper on the color properties of lead and aluminosilicate glasses by using optical and electron paramagnetic resonance (EPR) spectroscopies. Optical absorption spectra unveil distinct UV absorption characteristics in blue and green compounds, attributed to Cu+ ions, with notable variations depending on glass composition. EPR quantification of copper oxidation states reveals correlations with color variations, particularly evident in UV absorption shifts towards green colors at lower Cu2+ ratios. Redox analysis elucidates color differences in identical comp

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Gholam, Ali Montazer, and Davar Giveki. "Content based image retrieval system using clustered scale invariant feature transforms." optik 126 (June 7, 2015): 1695–99. https://doi.org/10.5281/zenodo.14013493.

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The large amounts of image collections available from a variety of sources have posed increasing technical challenges to computer systems to store/transmit and index/manage the image data to make such collections easily accessible.&lrm; To search and retrieve the expected images from the database a content-based image retrieval (CBIR) system is highly demanded.&lrm; CBIR extracts features of a query image and try to match them with extracted features from images in the database.&lrm; This paper introduces two novel methods as image descriptors.&lrm; The basis of the proposed methods is built u

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El khattabi, Zaynab, Youness Tabii, and Abdelhamid Benkaddour. "Video Shot Boundary Detection using the Scale Invariant Feature Transform and RGB Color Channels." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (2017): 2565. http://dx.doi.org/10.11591/ijece.v7i5.pp2565-2673.

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<p>Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of

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Zaynab, El khattabi, Tabii Youness, and Benkaddour Abdelhamid. "Video Shot Boundary Detection Using The Scale Invariant Feature Transform and RGB Color Channels." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (2017): 2565–73. https://doi.org/10.11591/ijece.v7i5.pp2565-2573.

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Segmentation of the video sequence by detecting shot changes is essential for video analysis, indexing and retrieval. In this context, a shot boundary detection algorithm is proposed in this paper based on the scale invariant feature transform (SIFT). The first step of our method consists on a top down search scheme to detect the locations of transitions by comparing the ratio of matched features extracted via SIFT for every RGB channel of video frames. The overview step provides the locations of boundaries. Secondly, a moving average calculation is performed to determine the type of transitio

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Reyrolle, Marine, Valérie Desauziers, Thierry Pigot, Lydia Gautier, and Mickael Le Bechec. "Comparison of Untargeted and Markers Analysis of Volatile Organic Compounds with SIFT-MS and SPME-GC-MS to Assess Tea Traceability." Foods 13, no. 24 (2024): 3996. https://doi.org/10.3390/foods13243996.

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Tea is one of the most consumed beverages in the world and presents a great aromatic diversity depending on the origin of the production and the transformation process. Volatile organic compounds (VOCs) greatly contribute to the sensory perception of tea and are excellent markers for traceability and quality. In this work, we analyzed the volatile organic compounds (VOCs) emitted by twenty-six perfectly traced samples of tea with two analytical techniques and two data treatment strategies. First, we performed headspace solid-phase microextraction gas chromatography–mass spectrometry (HS-SPME-G

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Liu, Zheng Dong, Hong Yun Xiong, and Ya Yan Wang. "Visual Search Method for Garment Image Based on SIFT." Applied Mechanics and Materials 333-335 (July 2013): 920–23. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.920.

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How to meet the customers requirement in product search is an import problem. Because the high-growing of e-commerce, a new demand emerges: the special-purpose search engine for searching goods from network shop. Our work focuses on the garment retrieval from the e-shopping database, which supports feature-based retrieval by shape categories and styles. This paper uses color and style characteristics of the garment images as a query information, based on the SIFT algorithm retrieval feature points of the garment image, and then using K-Means method to cluster the feature points. Use features t

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Dong, Wen-hui, Fa-liang Chang, and Tian-ping Li. "Adaptive Fragments-based Target Tracking Method Fusing Color Histogram and SIFT Features." Journal of Electronics & Information Technology 35, no. 4 (2014): 770–76. http://dx.doi.org/10.3724/sp.j.1146.2012.01095.

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Alitappeh, Reza Javanmard, Kossar Jeddi Saravi, and Fariborz Mahmoudi. "A New Illumination Invariant Feature Based on SIFT Descriptor in Color Space." Procedia Engineering 41 (2012): 305–11. http://dx.doi.org/10.1016/j.proeng.2012.07.177.

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Biglari, Osameh, Reza Ahsan, and Majid Rahi. "Human Detection Using Surf And Sift Feature Extraction Methods In Different Color Spaces." Journal of Mathematics and Computer Science 11, no. 02 (2014): 111–22. http://dx.doi.org/10.22436/jmcs.011.02.04.

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ODAKI, Tsutomu, Kazuaki HASHIMOTO, and Yoshitomo TODA. "The Color Sift of Cerium Molybdenum Sheelite by Substituting Bi3+ or W6+ Ion." Shikizai Kyokaishi 81, no. 3 (2008): 73–79. http://dx.doi.org/10.4011/shikizai.81.73.

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Zheng, Zhi Hui, and Bo Wang. "On-Road Vehicle Detection Based on Color Segmentation and Tracking Using Harris-SIFT." Advanced Materials Research 433-440 (January 2012): 5334–38. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.5334.

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This paper proposes a novel method for vehicle detection and tracking using a vehicle-mounted monocular camera in an intelligent vehicle system. Speed-based Adaptive Perception Zone (APZ) is first defined to ensure that the vehicle minimizes the spatial extent of the region it perceives according to its own speed. Vehicle candidates are generated using brake lights detection through color segmentation method and verified by a rule-based clustering approach. A tracking-by-detection scheme based on Harris-SIFT feature matching is then used to learn the template of the detected vehicle on line, l

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Palacios-Cabrera, Héctor, Karina Jimenes-Vargas, Mario González, Omar Flor-Unda, and Belén Almeida. "Determination of Moisture in Rice Grains Based on Visible Spectrum Analysis." Agronomy 12, no. 12 (2022): 3021. http://dx.doi.org/10.3390/agronomy12123021.

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Rice grain production is important for the world economy. Determining the moisture content of the grains, at several stages of production, is crucial for controlling the quality, safety, and storage of the grain. This work inspects how well rice images from global and local descriptors work for determining the moisture content of the grains using artificial vision and intelligence techniques. Three sets of images of rice grains from the INIAP 12 variety (National Institute of Agricultural Research of Ecuador) were captured with a mobile camera. The first one with natural light and the other on

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Efendi, Muhamad Masjun, Rosidin Rosidin, and Erfan Wahyudi. "Metode Algoritma SIFT dan Histogram Color RGB Untuk Analisis Manipulasi Copy-Move pada Citra Digital." EXPLORE 9, no. 1 (2019): 31. http://dx.doi.org/10.35200/explore.v9i1.106.

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Dengan kecanggihan teknologi sekarang ini menyebabkan citra digital dengan mudah dapat dimanipulasi. Manipulasi gambar dilakukan dengan cara menambahkan atau menghapus beberapa elemen dari gambar yang menghasilkan sejumlah pemalsuan citra yang tidak dapat diperhatikan oleh mata manusia. Hal ini juga didukung dengan tersedianya software editing gambar yang mudah digunkan, sehingga semua orang bisa melakukan manipulasi citra. Pemalsuan citra copy-move adalah jenis pemalsuan citra yang paling umum digunakan karena tekniknya yang mudah dilakukan oleh banyak orang dengan cara bagian dari gambar itu

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Mamadou, Diarra, Kacoutchy Jean Ayikpa, Abou Bakary Ballo, Nagbégna Diabate, and N’guessan Patrice Akoguhi. "Enhancing Face Recognition Performance with Multispectral Imaging and Machine Learning: Comparison from Sift and Sift-Freak Feature Extraction." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8s (2023): 329–40. http://dx.doi.org/10.17762/ijritcc.v11i8s.7213.

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The development of modern societies faces many security and identification challenges. To meet this expectation, computer vision offers biometric solutions. Much research in recent years has focused on face recognition. Traditional facial recognition that uses color images has had many shortcomings, such as variation in illumination, smoke, rain, disguise, face concealment, makeup, etc. Light-insensitive infrared (IR) imaging is presented as an alternative to facial recognition in the visible to overcome the shortcomings of uncontrolled environments. However, IR also has weaknesses, such as fa

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Anjali, Diwan, Sharma Rajat, K. Roy Anil, and K. Mitra Suman. "Digital Image Tamperin Gdetection using sift Key-Point." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 1484–89. https://doi.org/10.35940/ijeat.B3761.029320.

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Copy-move imitation is a widespread and generally utilized operation to corrupt digital image. It is considered as the most effective research areas in the domain of blind digital image forensics area. Key point based totally identification techniques have been regarded to be very environment-friendly in exposing copy-move proof because of their steadiness against a number of attacks, as like large-scale geometric movements. Conversely, these techniques don’t have the capabilities to cope with the instances if copy-move forgeries only engage in minor or clean areas, the place the quantit

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Manandhar, Prajowal, Ahmad Jalil, Khaled AlHashmi, and Prashanth Marpu. "Automatic Generation of Seamless Mosaics Using Invariant Features." Remote Sensing 13, no. 16 (2021): 3094. http://dx.doi.org/10.3390/rs13163094.

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The acquisition of satellite images over a wide area is often carried out across seasons because of satellite orbits and atmospheric conditions (e.g., cloud cover, dust, etc.). This results in spectral mismatch between adjacent scenes as the sun angle and the atmospheric conditions will be different for different acquisitions. In this work, we developed an approach to generate seamless mosaics using Scale-Invariant Features Transformation (SIFT). In this process, we make use of the overlapping areas between two adjacent scenes and then map spectral values of one imagery scene to another based

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AI, Dan-ni, Xian-hua HAN, Guifang DUAN, Xiang RUAN, and Yen-wei CHEN. "Global Selection vs Local Ordering of Color SIFT Independent Components for Object/Scene Classification." IEICE Transactions on Information and Systems E94-D, no. 9 (2011): 1800–1808. http://dx.doi.org/10.1587/transinf.e94.d.1800.

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Kalpana, J., and R. Krishnamoorthi. "Color image retrieval technique with local features based on orthogonal polynomials model and SIFT." Multimedia Tools and Applications 75, no. 1 (2014): 49–69. http://dx.doi.org/10.1007/s11042-014-2262-1.

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