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Journal articles on the topic 'Binary robust invariant scalable keypoints'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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1

JING, Huiyun, Xin HE, Qi HAN, and Xiamu NIU. "CBRISK: Colored Binary Robust Invariant Scalable Keypoints." IEICE Transactions on Information and Systems E96.D, no. 2 (2013): 392–95. http://dx.doi.org/10.1587/transinf.e96.d.392.

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Yang, Shuqiang, Biao Li, and Kun Zeng. "SBRISK: speed-up binary robust invariant scalable keypoints." Journal of Real-Time Image Processing 12, no. 3 (2014): 583–91. http://dx.doi.org/10.1007/s11554-014-0434-x.

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AboElenain, Eman, Khalid Amin, and Sameh Zarif. "Static video summarization approach using Binary Robust Invariant Scalable Keypoints." IJCI. International Journal of Computers and Information 8, no. 2 (2021): 125–30. http://dx.doi.org/10.21608/ijci.2021.207855.

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Liu, Yanli, Heng Zhang, Hanlei Guo, and Neal Xiong. "A FAST-BRISK Feature Detector with Depth Information." Sensors 18, no. 11 (2018): 3908. http://dx.doi.org/10.3390/s18113908.

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RGB-D cameras offer both color and depth images of the surrounding environment, making them an attractive option for robotic and vision applications. This work introduces the BRISK_D algorithm, which efficiently combines Features from Accelerated Segment Test (FAST) and Binary Robust Invariant Scalable Keypoints (BRISK) methods. In the BRISK_D algorithm, the keypoints are detected by the FAST algorithm and the location of the keypoint is refined in the scale and the space. The scale factor of the keypoint is directly computed with the depth information of the image. In the experiment, we have

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Singh, Amarpreet, and Sanjogdeep Singh. "Gray Level Co-occurrence Matrix with Binary Robust Invariant Scalable Keypoints for Detecting Copy Move Forgeries." Journal of Image and Graphics 11, no. 1 (2023): 82–90. http://dx.doi.org/10.18178/joig.11.1.82-90.

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With advancement in technology, especially in imaging field, digital image forgery has increased a lot nowadays. In order to counter this problem, many forgery detection techniques have been developed from time to time. For rapid and accurate detection of forged image, a novel hybrid technique is used in this research work that implements Gray Level Co-occurrence Matrix (GLCM) along with Binary Robust Invariant Scalable Keypoints (BRISK). GLCM significantly extracts key attributes from an image efficiently which will help to increase the detection accuracy. BRISK is known to be one of the 3 fa

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ISIK, Murat. "Comprehensive empirical evaluation of feature extractors in computer vision." PeerJ Computer Science 10 (November 4, 2024): e2415. http://dx.doi.org/10.7717/peerj-cs.2415.

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Feature detection and matching are fundamental components in computer vision, underpinning a broad spectrum of applications. This study offers a comprehensive evaluation of traditional feature detections and descriptors, analyzing methods such as Scale Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF), Binary Robust Independent Elementary Features (BRIEF), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Invariant Scalable Keypoints (BRISK), KAZE, Accelerated KAZE (AKAZE), Fast Retina Keypoint (FREAK), Dense and Accurate Invariant Scalable descriptor for Yale (DAISY), F

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Kok, Kai Yit, and Parvathy Rajendran. "A Descriptor-Based Advanced Feature Detector for Improved Visual Tracking." Symmetry 13, no. 8 (2021): 1337. http://dx.doi.org/10.3390/sym13081337.

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Despite years of work, a robust, widely applicable generic “symmetry detector” that can paral-lel other kinds of computer vision/image processing tools for the more basic structural charac-teristics, such as a “edge” or “corner” detector, remains a computational challenge. A new symmetry feature detector with a descriptor is proposed in this paper, namely the Simple Robust Features (SRF) algorithm. A performance comparison is made among SRF with SRF, Speeded-up Robust Features (SURF) with SURF, Maximally Stable Extremal Regions (MSER) with SURF, Harris with Fast Retina Keypoint (FREAK), Minimu

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Jatmiko, D. A., and S. U. Prini. "Study and Performance Evaluation Binary Robust Invariant Scalable Keypoints (BRISK) for Underwater Image Stitching." IOP Conference Series: Materials Science and Engineering 879 (August 7, 2020): 012111. http://dx.doi.org/10.1088/1757-899x/879/1/012111.

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Gao, Junchai, and Zhen Sun. "An Improved ASIFT Image Feature Matching Algorithm Based on POS Information." Sensors 22, no. 20 (2022): 7749. http://dx.doi.org/10.3390/s22207749.

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The affine scale-invariant feature transform (ASIFT) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). However, there are many problems in the matching process, such as the low efficiency and mismatching. In order to improve the matching efficiency, this algorithm firstly simulates image distortion based on the position and orientation system (POS) information from real-time UAV measurements to reduce the number of simulated images. Then, the scale-invariant feature transform (SIFT

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Rebouças Filho, Pedro Pedrosa, Francisco Diego Lima Moreira, Leandro Bezerra Marinho, and Jefferson Silva Almeida. "Novel and powerful mosaic constructor for territorial analysis using mobile robots via Binary Robust Invariant Scalable Keypoints." Measurement 114 (January 2018): 448–70. http://dx.doi.org/10.1016/j.measurement.2017.10.007.

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Reddy, Shiva Shankar, Veeranki V. R. Maheswara Rao, Kalidindi Sravani, and Silpa Nrusimhadri. "Image quality evaluation: evaluation of the image quality of actual images by using machine learning models." Bulletin of Electrical Engineering and Informatics 13, no. 2 (2024): 1172–82. http://dx.doi.org/10.11591/eei.v13i2.5947.

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Evaluating image features is a significant step in image processing in applications like number plate detection, vehicle tracking and many image processing-based applications. Image processing-based applications need accurate parts to get the best outcomes. Feature detection is done based on various feature detection techniques. The proposed system aims to get the best feature detector based on the input images by evaluating the image features. For assessing the image features, the proposed system worked on various descriptors like oriented FAST and rotated brief (ORB), learned arrangements of

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Zhu, Yaguang, Chaoyu Jia, Chao Ma, and Qiong Liu. "SURF-BRISK–Based Image Infilling Method for Terrain Classification of a Legged Robot." Applied Sciences 9, no. 9 (2019): 1779. http://dx.doi.org/10.3390/app9091779.

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In this study, we propose adaptive locomotion for an autonomous multilegged walking robot, an image infilling method for terrain classification based on a combination of speeded up robust features, and binary robust invariant scalable keypoints (SURF-BRISK). The terrain classifier is based on the bag-of-words (BoW) model and SURF-BRISK, both of which are fast and accurate. The image infilling method is used for identifying terrain with obstacles and mixed terrain; their features are magnified to help with recognition of different complex terrains. Local image infilling is used to improve low a

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S., Indhumathi, and Christopher Clement J. "Convex-based lightweight feature descriptor for Augmented Reality Tracking." PLOS ONE 19, no. 7 (2024): e0305199. http://dx.doi.org/10.1371/journal.pone.0305199.

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Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. We have developed two filters capable of computing pixel intensity variations, followed by the covariance matrix of the polynomial to describe the features. The superiority of CBFD is validated through precision, recall, computation time, and feature location distance. Additionally, we provide a solution to determine the optimal block size for describ

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Jeyapal, Akilandeswari, Jothi Ganesan, Sabeenian Royappan Savarimuthu, et al. "A Comparative Study of Feature Detection Techniques for Navigation of Visually Impaired Person in an Indoor Environment." Journal of Computational and Theoretical Nanoscience 17, no. 1 (2020): 21–26. http://dx.doi.org/10.1166/jctn.2020.8623.

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A development of automatic location identification and tracking system for visually impaired/ challenged person is a very challenging task in an indoor environment. In this paper, the comprehensive study of different feature detection and matching techniques namely, Minimum Eigenvalue (MinEigen) algorithm, Harris–Stephens (Harris) algorithm, Speeded Up Robust Features (SURF), Features from Accelerated Segment Test (FAST), Binary Robust Invariant Scalable Keypoints (BRISK) and Maximally Stable Extremal Regions (MSER) is presented. These algorithms are employed to detect and match the features o

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Khin, Mar Thi. "Face Recognition for Human Identification using BRISK Feature and Normal Distribution Model." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 1139–43. https://doi.org/10.5281/zenodo.3590557.

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Face recognition is a kind of automatic human identification from face images has been performed widely research in image processing and machine learning. Face image, facial information of the person is presented and unique information for each person even two person possessed the same face. We propose a methodology for automatic human classification based on Binary Robust Invariant Scalable Keypoints BRISK feature of face images and the normal distribution model. In our proposed methodology, the normal distribution model is used to represent the statistical information of face image as a glob

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Mc’Okeyo, P. O., F. Nex, C. Persello, and A. Vrieling. "AUTOMATED CO-REGISTRATION OF INTRA-EPOCH AND INTER-EPOCH SERIES OF MULTISPECTRAL UAV IMAGES FOR CROP MONITORING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 309–16. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-309-2020.

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Abstract. The application of UAV-based aerial imagery has advanced exponentially in the past two decades. This can be attributed to UAV operational flexibility, ultra-high spatial resolution, inexpensiveness, and UAV-based sensors enhancement. Nonetheless, the application of multitemporal series of multispectral UAV imagery still suffers significant misregistration errors, and therefore becoming a concern for applications such as precision agriculture. Direct image georeferencing and co-registration is commonly done using ground control points; this is usually costly and time consuming. This r

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Li, Bo, Xiangfeng Wang, Qiang Gao, Zhimei Song, Cunyu Zou, and Siyuan Liu. "A 3D Scene Information Enhancement Method Applied in Augmented Reality." Electronics 11, no. 24 (2022): 4123. http://dx.doi.org/10.3390/electronics11244123.

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Aiming at the problem that the detection of small planes with unobvious texture is easy to be missed in augmented reality scene, a 3D scene information enhancement method to grab the planes for augmented reality scene is proposed based on a series of images of a real scene taken by a monocular camera. Firstly, we extract the feature points from the images. Secondly, we match the feature points from different images, and build the three-dimensional sparse point cloud data of the scene based on the feature points and the camera internal parameters. Thirdly, we estimate the position and size of t

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Fouad, Haidy S., and Hend A. Elsayed. "Evaluation of GAM Classifier Performance for Airplane Remote Sensing Images Based on SIFT Features." Journal of Image and Graphics 12, no. 2 (2024): 168–67. http://dx.doi.org/10.18178/joig.12.2.158-167.

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Remote sensing technology and its applications have attracted the attention of researchers. Background variation and the small objects in remote sensing images make the classification process a challenging task. In several domains, Generalized Additive Models (GAMs) have demonstrated their ability to capture nonlinear interactions between explanatory variables and a response variable. This research evaluates the GAM with Scale Invariant Feature Transform (SIFT) for airplane remote sensing image classification. SIFT is a widely used local feature detection algorithm that performs best under sca

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Jana, Ayanabha, and Shridevi S. Krishnakumar. "Sign Language Gesture Recognition with Convolutional-Type Features on Ensemble Classifiers and Hybrid Artificial Neural Network." Applied Sciences 12, no. 14 (2022): 7303. http://dx.doi.org/10.3390/app12147303.

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The proposed research deals with constructing a sign gesture recognition system to enable improved interaction between sign and non-sign users. With respect to this goal, five types of features are utilized—hand coordinates, convolutional features, convolutional features with finger angles, convolutional features on hand edges and convolutional features on binary robust invariant scalable keypoints—and trained on ensemble classifiers to accurately predict the label of the sign image provided as input. In addition, a hybrid artificial neural network is also fabricated that takes two of the afor

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Zhang, Jiali. "Research on the algorithm of image feature detection and matching." Applied and Computational Engineering 5, no. 1 (2023): 527–35. http://dx.doi.org/10.54254/2755-2721/5/20230636.

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In-depth research on feature detection technology affects people's modern life. Modern artificial intelligence can act as the eyes of human beings and efficiently filter out effective information from complex pictures. Corner detection has now evolved into a tool for efficient image scanning. People's increasingly stringent requirements for image processing continue to promote the birth of new technologies. Corner detection methods have been improved and perfected, and have experienced detectors such as Harris, FAST, Scalriant Feature Transform (SIFT), Speeded Up Robust Feature (SURF), Binary

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Oliveira, António José, Bruno Miguel Ferreira, and Nuno Alexandre Cruz. "A Performance Analysis of Feature Extraction Algorithms for Acoustic Image-Based Underwater Navigation." Journal of Marine Science and Engineering 9, no. 4 (2021): 361. http://dx.doi.org/10.3390/jmse9040361.

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In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise and multiple secondary echoes. In recent years, research has been conducted regarding the application of feature extraction algorithms to underwater acoustic images, with the purpose of achieving a robust solution for the detection and matching of environment

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Silvia, Joseph, Hipiny Irwandi, and Ujir Hamimah. "Iban plaited mat motif classification with adaptive smoothing." International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (2023): 840–50. https://doi.org/10.11591/ijai.v12.i2.pp840-850.

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Decorative mats plaited by the Iban communities in Borneo contains motifs that reflect their traditional beliefs. Each motif has its own special meaning and taboos. A typical mat motif contains multiple smaller patterns that surround the main motif hence is likely to cause misclassification. We introduce a classification framework with adaptive sampling to remove smaller features whilst retaining larger (and discriminative) image structures. Canny filter and probabilistic hough transform are gradually applied to a clean greyscale image until a threshold value pertaining to the image’s st

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Susilawati Mohamad, Fatma, Fadi Mohammad Alsuhimat, Mohamad Afendee Mohamed, Mumtazimah Mohamad, and Azrul Amri Jamal. "Detection and Feature Extraction for Images Signatures." International Journal of Engineering & Technology 7, no. 3.28 (2018): 44. http://dx.doi.org/10.14419/ijet.v7i3.28.20963.

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The signing process is one of the most important processes used by organizations to ensure the confidentiality of information and to protect it against any unauthorized penetration or access to such information. As organizations and individuals enter the digital world, there is an urgent need for a digital system capable of distinguishing between the original and fraud signature, in order to ensure individuals authorization and determine the powers allowed to them. In this paper, three widely used feature detection algorithms, HARRIS, BRISK (Binary Robust Invariant Scalable Keypoints) and FAST

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Kashihara, Koji. "An Intelligent Computer Assistance System for Artifact Restoration Based on Genetic Algorithms with Plane Image Features." International Journal of Computational Intelligence and Applications 16, no. 03 (2017): 1750021. http://dx.doi.org/10.1142/s1469026817500213.

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Restoration work of archaeological artifacts broken into pieces is similar to putting together a jigsaw puzzle. The purpose of this study is to construct an intelligent computer assistance system to conveniently restore archaeological discoveries from some fragments. AReal-Coded Genetic Algorithm (RCGA) was applicable for solving the positioning problem of a three-dimensional (3D) restoration. The fitness function value for RCGA was calculated from image similarity between the target and correct patterns in plane images at multiple camera angles. Image features of a 3D object were obtained by

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Joseph, Silvia, Irwandi Hipiny, and Hamimah Ujir. "Iban plaited mat motif classification with adaptive smoothing." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (2023): 840. http://dx.doi.org/10.11591/ijai.v12.i2.pp840-850.

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<span lang="EN-US">Decorative mats plaited by the Iban communities in Borneo contains motifs that reflect their traditional beliefs. Each motif has its own special meaning and taboos. A typical mat motif contains multiple smaller patterns that surround the main motif hence is likely to cause misclassification. We introduce a classification framework with adaptive sampling to remove smaller features whilst retaining larger (and discriminative) image structures. Canny filter and probabilistic hough transform are gradually applied to a clean greyscale image until a threshold value pertainin

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Gao, Han, Zhangqin Huang, Huapeng Yang, Xiaobo Zhang, and Chen Cen. "Research on Improved Multi-Channel Image Stitching Technology Based on Fast Algorithms." Electronics 12, no. 7 (2023): 1700. http://dx.doi.org/10.3390/electronics12071700.

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The image registration and fusion process of image stitching algorithms entails significant computational costs, and the use of robust stitching algorithms with good performance is limited in real-time applications on PCs (personal computers) and embedded systems. Fast image registration and fusion algorithms suffer from problems such as ghosting and dashed lines, resulting in suboptimal display effects on the stitching. Consequently, this study proposes a multi-channel image stitching approach based on fast image registration and fusion algorithms, which enhances the stitching effect on the b

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Liu, Qiong, JiZhuang Hui, Li Luo, and YanPu Yang. "Target Identification and Location Algorithm Based on SURF-BRISK Operator." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 06 (2016): 1655016. http://dx.doi.org/10.1142/s0218001416550168.

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Accurate and fast target image recognition is an important function of applications such as remote sensing imaging and medical imaging. However, an operator such as speeded up robust feature (SURF) cannot be accurately matched in the recognition process of a target image. This led us to propose the use of a method capable of matching identification, i.e. binary robust invariant scalable keypoints (BRISK) operators, in combination with SURF operators. The proposed algorithm combines the accuracy of SURF operators and the rapidity of BRISK operators to obtain a quick and accurate way of matching

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Tao, Chongben, Yufeng Jin, Feng Cao, Zufeng Zhang, Chunguang Li, and Hanwen Gao. "3D Semantic VSLAM of Indoor Environment Based on Mask Scoring RCNN." Discrete Dynamics in Nature and Society 2020 (October 20, 2020): 1–14. http://dx.doi.org/10.1155/2020/5916205.

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In view of existing Visual SLAM (VSLAM) algorithms when constructing semantic map of indoor environment, there are problems with low accuracy and low label classification accuracy when feature points are sparse. This paper proposed a 3D semantic VSLAM algorithm called BMASK-RCNN based on Mask Scoring RCNN. Firstly, feature points of images are extracted by Binary Robust Invariant Scalable Keypoints (BRISK) algorithm. Secondly, map points of reference key frame are projected to current frame for feature matching and pose estimation, and an inverse depth filter is used to estimate scene depth of

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Zhou, Xiaoteng, Shihao Yuan, Changli Yu, Hongyuan Li, and Xin Yuan. "Performance Comparison of Feature Detectors on Various Layers of Underwater Acoustic Imagery." Journal of Marine Science and Engineering 10, no. 11 (2022): 1601. http://dx.doi.org/10.3390/jmse10111601.

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Image feature matching is essential in many computer vision applications, and the foundation of matching is feature detection, which is a crucial feature quantification process. This manuscript focused on detecting more features from underwater acoustic imageries for further ocean engineering applications of autonomous underwater vehicles (AUVs). Currently, the mainstream feature detection operators are developed for optical images, and there is not yet a feature detector oriented to underwater acoustic imagery. To better analyze the suitability of existing feature detectors for acoustic image

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Singh, Nagendra Pratap, and Vibhav Prakash Singh. "Efficient Segmentation and Registration of Retinal Image Using Gumble Probability Distribution and BRISK Feature." Traitement du Signal 37, no. 5 (2020): 855–64. http://dx.doi.org/10.18280/ts.370519.

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The registration of segmented retinal images is mainly used for the diagnosis of various diseases such as glaucoma, diabetes, and hypertension, etc. These retinal diseases depend on the retinal vessel structure. The fast and accurate registration of segmented retinal images helps to identify the changes in vessels and the diagnosis of the diseases. This paper presents a novel binary robust invariant scalable key point (BRISK) feature-based segmented retinal image registration approach. The BRISK framework is an efficient keypoint detection, description, and matching approach. The proposed appr

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Yan, Hai’an, Jian Wang, and Peng Zhang. "Application of Optimized ORB Algorithm in Design AR Augmented Reality Technology Based on Visualization." Mathematics 11, no. 6 (2023): 1278. http://dx.doi.org/10.3390/math11061278.

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The current media digitization and artistic strength are more powerful than the previous application. Using its advanced information display methods and technologies, this paper proposed a digital museum built by integrating digital media art with AR technology, which was helpful to analyze and solve the objective problems of current museums’ ecological imbalance and single-system function. Based on the principles and laws of augmented reality technology, the museum guide system is optimized. In the system evaluation experiment, firstly, the cultural relics of six kinds of materials are used a

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Sayed Ismail, Sharifah Noor Masidayu, Nor Azlina Ab. Aziz, Siti Zainab Ibrahim, et al. "Evaluation of electrocardiogram: numerical vs. image data for emotion recognition system." F1000Research 10 (May 30, 2022): 1114. http://dx.doi.org/10.12688/f1000research.73255.2.

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Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using 2- D ECG. Numerous studies have proven that ECG can be used to detect human emotions using 1-D ECG; however, ECG is typically captured as 2-D images rather than as 1-D data. There is still no consensus on the effect of the ECG input format on the accuracy of the emotion recognition system (ERS). The ERS using 2-D ECG is still inadequately studied. Therefore, this study compared ERS performance using 1-D and 2-D ECG data to investigate the effect of the ECG input

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Sayed Ismail, Sharifah Noor Masidayu, Nor Azlina Ab. Aziz, Siti Zainab Ibrahim, et al. "Evaluation of electrocardiogram: numerical vs. image data for emotion recognition system." F1000Research 10 (November 4, 2021): 1114. http://dx.doi.org/10.12688/f1000research.73255.1.

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Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using ECG wave images. Numerous studies have proven that ECG can be used to detect human emotions using numerical data; however, ECG is typically captured as a wave image rather than as a numerical data. There is still no consensus on the effect of the ECG input format (either as an image or a numerical value) on the accuracy of the emotion recognition system (ERS). The ERS using ECG images is still inadequately studied. Therefore, this study compared ERS performance u

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Zhang, Jiaming, Xuejuan Hu, Tan Zhang, et al. "Binary Neighborhood Coordinate Descriptor for Circuit Board Defect Detection." Electronics 12, no. 6 (2023): 1435. http://dx.doi.org/10.3390/electronics12061435.

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Due to the periodicity of circuit boards, the registration algorithm based on keypoints is less robust in circuit board detection and is prone to misregistration problems. In this paper, the binary neighborhood coordinate descriptor (BNCD) is proposed and applied to circuit board image registration. The BNCD consists of three parts: neighborhood description, coordinate description, and brightness description. The neighborhood description contains the grayscale information of the neighborhood, which is the main part of BNCD. The coordinate description introduces the actual position of the keypo

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Xue, Mingfu, Chengxiang Yuan, Zhe Liu, and Jian Wang. "SSL: A Novel Image Hashing Technique Using SIFT Keypoints with Saliency Detection and LBP Feature Extraction against Combinatorial Manipulations." Security and Communication Networks 2019 (March 3, 2019): 1–18. http://dx.doi.org/10.1155/2019/9795621.

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Image hashing schemes have been widely used in content authentication, image retrieval, and digital forensic. In this paper, a novel image hashing algorithm (SSL) by incorporating the most stable keypoints and local region features is proposed, which is robust against various content-preserving manipulations, even multiple combinatorial manipulations. The proposed algorithm combines S_cale invariant feature transform (SIFT) with S_aliency detection to extract the most stable keypoints. Then, the L_ocal binary pattern (LBP) feature extraction method is exploited to generate local region feature

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CUI Shao-hui, 崔少辉, 谢征 XIE Zheng, 王刚 WANG Gang, and 陈鹏 CHEN Peng. "Feature matching electronic image stabilization based on binary robust invariant scalable keypionts." Optics and Precision Engineering 23, no. 9 (2015): 2715–23. http://dx.doi.org/10.3788/ope.20152309.2715.

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Jang, Dong-Hwa, Kyeong-Seok Kwon, Jung-Kon Kim, Ka-Young Yang, and Jong-Bok Kim. "Dog Identification Method Based on Muzzle Pattern Image." Applied Sciences 10, no. 24 (2020): 8994. http://dx.doi.org/10.3390/app10248994.

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Currently, invasive and external radio frequency identification (RFID) devices and pet tags are widely used for dog identification. However, social problems such as abandoning and losing dogs are constantly increasing. A more effective alternative to the existing identification method is required and the biometrics can be the alternative. This paper proposes an effective dog muzzle recognition method to identify individual dogs. The proposed method consists of preprocessing, feature extraction, matching, and postprocessing. For preprocessing, proposed resize and histogram equalization are used

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Gajic, Dusan, Gorana Gojic, Dinu Dragan, and Veljko Petrovic. "Comparative evaluation of keypoint detectors for 3d digital avatar reconstruction." Facta universitatis - series: Electronics and Energetics 33, no. 3 (2020): 379–94. http://dx.doi.org/10.2298/fuee2003379g.

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Three-dimensional personalized human avatars have been successfully utilized in shopping, entertainment, education, and health applications. However, it is still a challenging task to obtain both a complete and highly detailed avatar automatically. One approach is to use general-purpose, photogrammetry-based algorithms on a series of overlapping images of the person. We argue that the quality of avatar reconstruction can be increased by modifying parts of the photogrammetry-based algorithm pipeline to be more specifically tailored to the human body shape. In this context, we perform an extensi

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Fung, Wai Tong, and Kin Man Lam. "A robust and efficient automated product recognition system based on scenario design methodology and computer vision techniques." HKIE Transactions 29, no. 1 (2022): 70–87. http://dx.doi.org/10.33430/v29n1thie-2020-0003.

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Automated product recognition systems should minimise the online product verification time while keeping product recognition robust to human interventions, including misplaced products, rotated products and empty shelves. A predefined template of each product is generated offline, and scale and location invariant binary local features are employed for recognition. Three types of Sampling Bounding Mask (SBM) are defined and combined with RGB/LUV colour histograms, and matched with a planar level of a shelf by using the Earth Mover’s Distance, thereby reducing the computation time by 50%. Eight

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Li, Bangjie, Dongdong Guan, Xiaolong Zheng, Zhengsheng Chen, and Lefei Pan. "SD-CapsNet: A Siamese Dense Capsule Network for SAR Image Registration with Complex Scenes." Remote Sensing 15, no. 7 (2023): 1871. http://dx.doi.org/10.3390/rs15071871.

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SAR image registration is the basis for applications such as change detection, image fusion, and three-dimensional reconstruction. Although CNN-based SAR image registration methods have achieved competitive results, they are insensitive to small displacement errors in matched point pairs and do not provide a comprehensive description of keypoint information in complex scenes. In addition, existing keypoint detectors are unable to obtain a uniform distribution of keypoints in SAR images with complex scenes. In this paper, we propose a texture constraint-based phase congruency (TCPC) keypoint de

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Cheng, Min-Lung, and Masashi Matsuoka. "An Efficient and Precise Remote Sensing Optical Image Matching Technique Using Binary-Based Feature Points." Sensors 21, no. 18 (2021): 6035. http://dx.doi.org/10.3390/s21186035.

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Matching local feature points is an important but crucial step for various optical image processing applications, such as image registration, image mosaicking, and structure-from-motion (SfM). Three significant issues associated with this subject have been the focus for years, including the robustness of the image features detected, the number of matches obtained, and the efficiency of the data processing. This paper proposes a systematic algorithm that incorporates the synthetic-colored enhanced accelerated binary robust invariant scalar keypoints (SC-EABRISK) method and the affine transforma

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Huang, Hao, Xuebin Wang, Yongbiao Hu, and Peng Tan. "Accuracy Analysis of Visual Odometer for Unmanned Rollers in Tunnels." Electronics 12, no. 20 (2023): 4202. http://dx.doi.org/10.3390/electronics12204202.

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Rollers, integral to road construction, are undergoing rapid advancements in unmanned functionality. To address the specific challenge of unmanned compaction within tunnels, we propose a vision-based odometry system for unmanned rollers. This system solves the problem of tunnel localization under conditions of low texture and high noise. We evaluate and compare the performance of various feature extraction and matching methods, followed by the application of random sample consensus (RANSAC) to eliminate false matches. Subsequently, Perspective-n-Points (PnP) was employed to establish a minimal

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Melek, Ceren Gulra, Elena Battini Sonmez, Hakan Ayral, and Songul Varli. "Development of a Hybrid Method for Multi-Stage End-to-End Recognition of Grocery Products in Shelf Images." Electronics 12, no. 17 (2023): 3640. http://dx.doi.org/10.3390/electronics12173640.

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Product recognition on grocery shelf images is a compelling task of object detection because of the similarity between products, the presence of the different scale of product sizes, and the high number of classes, in addition to constantly renewed packaging and added new products’ difficulty in data collection. The use of conventional methods alone is not enough to solve a number of retail problems such as planogram compliance, stock tracking on shelves, and customer support. The purpose of this study is to achieve significant results using the suggested multi-stage end-to-end process, includ

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H, Shridhar, S. Harakannanavar Sunil, Kanabur Vidyashree, and Jayalaxmi H. "Performance Analysis of Feature based Multiple Descriptors with Histogram Equalization for Image Mosaicing." Indian Journal of Science and Technology 16, no. 31 (2023): 2380–87. https://doi.org/10.17485/IJST/v16i31.433.

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Abstract <strong>Objectives:</strong> The main objective of the proposed work is to develop an image mosaicing model for combining the images of different individual images. In other way, the union of two images and to evaluate the performance of the model in terms of the number of run time in seconds and number of key features they use. <strong>Methods:</strong> In this work, the Histogram Equalization is a processing step required to make the mosaic invariant to intra image and inter image intensity variability. The detailed feature of the enhanced image is extracted using Sca

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Mahmud, Hasan, Md Kamrul Hasan, Abdullah-Al-Tariq, Md Hasanul Kabir, and M. A. Mottalib. "Recognition of Symbolic Gestures Using Depth Information." Advances in Human-Computer Interaction 2018 (November 19, 2018): 1–13. http://dx.doi.org/10.1155/2018/1069823.

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Symbolic gestures are the hand postures with some conventionalized meanings. They are static gestures that one can perform in a very complex environment containing variations in rotation and scale without using voice. The gestures may be produced in different illumination conditions or occluding background scenarios. Any hand gesture recognition system should find enough discriminative features, such as hand-finger contextual information. However, in existing approaches, depth information of hand fingers that represents finger shapes is utilized in limited capacity to extract discriminative fe

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Zarif, Sameh, Eman Morad, Khalid Amin, Abdullah Alharbi, Wail S. Elkilani, and Shouze Tang. "Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means." Computers, Materials & Continua, 2024, 1–10. http://dx.doi.org/10.32604/cmc.2024.046185.

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Shiva, Shankar Reddy, V. R. Maheswara Rao Veeranki, Sravani Kalidindi, and Nrusimhadri Silpa. "Image quality evaluation: evaluation of the image quality of actual images by using machine learning models." Bulletin of Electrical Engineering and Informatics (BEEI) 13, no. 2 (2024). https://doi.org/10.11591/eei.v13i2.5947.

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Evaluating image features is a significant step in image processing in applications like number plate detection, vehicle tracking and many image processing-based applications. Image processing-based applications need accurate parts to get the best outcomes. Feature detection is done based on various feature detection techniques. The proposed system aims to get the best feature detector based on the input images by evaluating the image features. For assessing the image features, the proposed system worked on various descriptors like oriented FAST and rotated brief (ORB), learned arrangements of

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Xu, Zhiniu, Xiaonan Wu, Yuxuan Liu, et al. "An improved BRISK‐FREAK‐based algorithm combined with LSD algorithm for complex pointer meter identification." IET Science, Measurement & Technology, July 21, 2024. http://dx.doi.org/10.1049/smt2.12204.

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AbstractTo locate and read the complex pointer meter dial for the images with uneven illumination, blurred dial, and tilted dial, this paper firstly proposes an improved BRISK‐FREAK algorithm for dial position. Then, combined with the Line Segment Detector (LSD) algorithm, an automatic identification method for complex pointer meter is proposed. The dial of a large number of SF6 complex pressure pointer meter images are located and the results reveal that the proposed improved BRISK‐FREAK algorithm has good adaptability under strong interference. The computational speed of the proposed algorit

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Kugunavar, Sneha, and C. J. Prabhakar. "Medical image retrieval using ROI extraction and hybrid bag-of-features model." Journal of Electrical Systems and Information Technology 12, no. 1 (2025). https://doi.org/10.1186/s43067-025-00228-7.

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Abstract Medical image processing is a vital component of modern healthcare, with content-based medical image retrieval (CBMIR) playing an increasingly important role. However, existing CBMIR methods still face challenges in handling multimodal datasets and large-scale image collections effectively. This paper proposes a novel CBMIR framework based on a hybrid bag-of-features model designed for improved scalability, interpretability, and retrieval performance. The approach integrates Bag-of-Visual-Words (BoVW) with shape and texture descriptors to enhance feature richness. Region of interest e

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Gu, Zunan, Ji Chen, and Chuansong Wu. "Three-Dimensional Reconstruction of Welding Pool Surface by Binocular Vision." Chinese Journal of Mechanical Engineering 34, no. 1 (2021). http://dx.doi.org/10.1186/s10033-021-00567-2.

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AbstractCurrent research of binocular vision systems mainly need to resolve the camera’s intrinsic parameters before the reconstruction of three-dimensional (3D) objects. The classical Zhang’ calibration is hardly to calculate all errors caused by perspective distortion and lens distortion. Also, the image-matching algorithm of the binocular vision system still needs to be improved to accelerate the reconstruction speed of welding pool surfaces. In this paper, a preset coordinate system was utilized for camera calibration instead of Zhang’ calibration. The binocular vision system was modified

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