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International Core Journal of Engineering 2021年第8期7卷 499-507页

作者： Jinsong Zhang Lei Tang Zhiyao Sun Jun Liao

Image mosaic technology has developed rapidly in recent years. The core of image mosaic is the processing method of image registration. sift algorithm has become a common method of image registration because of its simple and accurate characteristics. This paper reviews a large number of literatures and summarizes the general process of sift algorithm, which includes scale space construction, key point detection and elimination, key point direction assignment, key point description and key point matching. After these processing, the target image can be fused and reconstructed into a new image with a wide view angle and more information.

关键词： Image Mosaic Image Registration sift algorithm Feature Extraction

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Research on Global Motion Estimation Based on Adaptive sift algorithm

Research on Global Motion Estimation Based on Adaptive SIFT ...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Zhang, Huiqing An, Jiancheng Cao, Luguang Beijing Univ Technol Sch Elect Informat & Control Engn Beijing 100124 Peoples R China

ISBN: (纸本)9781467313988

Based on time redundancy in video image sequences an adaptive sift (Scale-invariant feature transform) algorithm is proposed. According to the latest three models' outputs in global motion estimation, the algorithm predicts overlapping regions between reference and current frames by using Lagrange parabolic interpolation, and then extracts feature points in the smaller region instead of the whole image. In this way, it can eliminate a large number of information redundancies to increase the processing speed of each frame, improve the effectiveness of feature points and reduce the mismatch. Experimental results show that the improved algorithm has the features of strong adaptive ability, rapidity and high matching accuracy, and it can be applied to the real-time positioning.

关键词： sift algorithm global motion estimation adaptive parabolic interpolation

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An Improved sift algorithm for Feature Points Matching of Dairy Cow Images

An Improved SIFT Algorithm for Feature Points Matching of Da...

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第三届国际计算机及计算技术农业应用学术会议

作者： Lizhong Wang Vocational and Technical College Inner Mongolia Agricultural university Hohhot,Inner Mongolia,China Shuoshi Ma College of Mechanical and Electrical Engineering Inner Mongolia Agricultural university Hohhot,Inner Mongolia,China Heru Xue and Zhenjie Hou College of Computer and Information Engineering Inner Mongolia Agricultural university Hohhot,Inner Mongolia,China

The conformation is the main parameter in dairy cow appraisal;hence,it is necessary for the measuring and evaluating of dairy conformation to use machine vision technology in 3D *** feature points detecting and matching are the pivotal steps in 3D *** conventional sift feature points matching algorithm has shortcomings of too large search area and low efficiency,An improved sift feature points matching algorithm is proposed to reduce the search range from both row and column directions based on binocular vision principle.2.7 times of in speed by the improved algorithm has been shown in the experiments compared with that of the conventional algorithm with the same matching precision.

关键词： diary cow conformation feature points detecting feature points matching sift algorithm

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Panorama Stitching Based on sift algorithm and Levenberg-Marquardt Optimization

Panorama Stitching Based on SIFT Algorithm and Levenberg-Mar...

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2010 International Colloquium on Computing,Communication, Control, and Management (CCCM2010)

作者： ZHONG Min College of Computer Information Engineering Jiangxi Normal University Nanchang,China ZENG Jiguo College of Computer Information Engineering Jiangxi Normal University Nanchang,China XIEXusheng College of Computer Information Engineering Jiangxi Normal University Nanchang,China

Panorama stitching algorithm based on scale invariant feature transform and Levenberg-Marquardt optimiza-tion is *** the source planar images to a cylind-rical surface is the first ***,correct matching feature pairs are detected between two images by sift and RANSAC algorithm. Finally the Levenberg-Marquardt algorithm is used for calculating the initial estimates of motion parameters. Experiment results show that this method is effective against the hand-held camera motion with small rotation around the optical axis,small horizontal and vertical movement.

关键词： panorama cylindrical projection sift algorithm Levenberg-Marquardt Optimization

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A New Kind of Anti-fake Label Application Based on sift algorithm

A New Kind of Anti-fake Label Application Based on SIFT Algo...

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2017 International Conference on Computer, Electronics and Communication Engineering(CECE2017)

作者： Jian LIU Shi-qing WANG Si-li LI The Engineering & Technical College of Chengdu University of Technology

The traditional anti-fake label is easy to fabricated because it has not a unique feature. To satisfy the trace-to-source requirement of nowadays, a new printed label was proposed which combined the advantages of unique QR code and physically unique texture feature of traditional texture label. Adopting sift algorithm, the texture feature of this kind of label was extracted and stored in database, and then labels were matched by using minimum Euclidean-distance method. Experimental Results showed that a good identification and matching accuracy can be obtained even labels' image were deformed. Finally, a new kind of anti-fake label system were completely conformed by texture paper and QR code, sift texture feature recognizing module, texture matching module, database and mobile phone App. In this paper, the emphasis was focused on the middle two parts.

关键词： Anti-fake label Texture feature recognition sift algorithm Minimum Euclidean-distance method

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An improved sift algorithm for Feature Points matching of dairy cow images

An improved SIFT Algorithm for Feature Points matching of da...

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亚洲精细农业与计算机农业应用联合大会

作者： Lizhong Wang Vocational and Technical College Inner Mongolia Agricultural university Hohhot, Inner Mongolia, China Shuoshi Ma College of Mechanical and Electrical Engineering Inner Mongolia Agricultural university Hohhot, Inner Mongolia, China Heru Xue Zhenjie Hou College of Computer and Information Engineering Inner Mongolia Agricultural university Hohhot, Inner Mongolia,China

The conformation is the main parameter in dairy cow appraisal;hence, it is necessary for the measuring and evaluating of dairy conformation to use machine vision technology in 3D reconstruction. The feature points detecting and matching are the pivotal steps in 3D reconstruction. The conventional sift feature points matching algorithm has shortcomings of too large search area and low efficiency, An improved sift feature points matching algorithm is proposed to reduce the search range from both row and column directions based on binocular vision principle. 2.7 times of in speed by the improved algorithm has been shown in the experiments compared with that of the conventional algorithm with the same matching precision.

关键词： diary cow conformation feature points detecting feature points matching sift algorithm

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An Improved sift Matching algorithm

An Improved SIFT Matching Algorithm

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International Conference on Measurement, Instrumentation and Automation (ICMIA 2012)

作者： Ding Can Qu Chang-wen Su Feng Naval Aeronaut & Astronaut Univ Dept Elect & Informat Engn Yantai 264001 Peoples R China

ISBN: (纸本)9783037855454

The high dimension and complexity of feature descriptor of Scale Invariant Feature Transform (sift), not only occupy the memory spaces, but also influence the speed of feature matching. We adopt the statistic feature point's neighbor gradient method, the local statistic area is constructed by 8 concentric square ring feature of points-centered, compute gradient of these pixels, and statistic gradient accumulated value of 8 directions, and then descending sort them, at last normalize them. The new feature descriptor descend dimension of feature from 128 to 64, the proposed method can improve matching speed and keep matching precision at the same time.

关键词： sift algorithm image matching feature descriptor DOG

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Fast sift algorithm based on Sobel Edge Detector

Fast SIFT Algorithm based on Sobel Edge Detector

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International Conference on Consumer Electronics, Communications and Networks

作者： Yang Li Lingshan Liu Lianghao Wang Dongxiao Li Ming Zhang Institute of Information and Communication Engineering Zhejiang University

ISBN: (纸本)9781457714146

The sift (Scale Invariant Feature Transform) algorithm is an approach for extracting distinctive invariant features from images. It is widely used in image matching. Since sift detector detects the extreme points through the whole scale space, it often selects keypoints that have no value and reduces the efficiency of the algorithm. This paper proposes a fast sift algorithm based on Sobel edge detector. Sobel edge detector is applied to generate an edge group scale space and sift detector detects the extreme point under the constraint of the edge group scale space. The experimental results show that the proposed algorithm decreases the redundancy of keypoints and speeds up the implementation while the matching rate between different images maintains at a high level. As the threshold of Sobel detector increases, number of keypoints decreases and matching rate gets higher.

关键词： sift algorithm Image matching Sobel edge detector Scale invariant

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Toward Efficient Edge Detection: A Novel Optimization Method Based on Integral Image Technology and Canny Edge Detection

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PROCESSES 2025年第2期13卷 293-293页

作者： Li, Yanqin Zhang, Dehai Zhengzhou Univ Light Ind Mech & Elect Engn Inst Zhengzhou 450002 Peoples R China Henan Key Lab Intelligent Mfg Mech Equipment Zhengzhou 450002 Peoples R China

The traditional sift (Scale Invariant Feature Transform) registration algorithm is highly regarded in the field of image processing due to its scale invariance, rotation invariance, and robustness to noise. However, it faces challenges such as a large number of feature points, high computational demand, and poor real-time performance when dealing with large-scale images. A novel optimization method based on integral image technology and canny edge detection is presented in this paper, aiming to maintain the core advantages of the sift algorithm while reducing the complexity involved in image registration computations, enhancing the efficiency of the algorithm for real-time image processing, and better adaption to the needs of large-scale image handling. Firstly, Gaussian separation techniques were used to simplify Gaussian filtering, followed by the application of integral image techniques to accelerate the construction of the entire pyramid. Additionally, during the feature point detection phase, an innovative feature point filtering strategy was introduced by combining Canny edge detection with dilation operations alongside the traditional sift approach, aiming to reduce the number of feature points and thereby lessen the computational load. The method proposed in this paper takes 0.0134 s for Image type a, 0.0504 s for Image type b, and 0.0212 s for Image type c. In contrast, the traditional method takes 0.1452 s for Image type a, 0.5276 s for Image type b, and 0.2717 s for Image type c, resulting in reductions of 0.1318 s, 0.4772 s, and 0.2505 s, respectively. A series of comparative experiments showed that the time taken to construct the Gaussian pyramid using our proposed method was consistently lower than that required by the traditional method, indicating greater efficiency and stability regardless of image size or type.

关键词： sift algorithm canny edge detection image registration Gaussian separation integral image

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A novel digital image correlation based on a reliable subset strategy for discontinuous displacement measurement

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OPTICS AND LASERS IN ENGINEERING 2025年 191卷

作者： Dong, Wei Wang, Xuebin Zhao, Guangchen Mao, Qiang Shanxi Inst Technol Dept Civil & Engn Yangquan 454000 Peoples R China Liaoning Tech Univ Coll Mech & Engn Fuxin 12300 Peoples R China Liaoning Tech Univ Inst Computat Mech Fuxin 12300 Peoples R China

Digital image correlation (DIC) is a widely employed method for deformation measurement. However, standard DIC is severely limited in discontinuous deformation measurement, because the shape functions used in standard DIC cannot accurately describe the discontinuous deformation of the subsets. In this paper, a reliable subset strategy is proposed to address discontinuities in DIC. In the implementation of this strategy, sift algorithm is utilized to match reference image and target images to obtain the reliable subsets. The reliable subset is a square region selected around matched feature points on reference image, which can avoid the discontinuous deformation regions. Then the reliable subset is correlated to obtain the exact deformation using the Gaussian weighted correlation function. Finally, the deformation parameters of a point of interest (POI) can be obtained by fitting the displacement of reliable subset centers for a fitting region around POI. In cases where discontinuities exist in the fitting region, the direct fitting method may yield substantial errors for obtaining POI deformation parameters. To ensure the accuracy of displacement measurements, the reliable subsets centers in the fitting region are classified into two categories along the crack face, and the most appropriate category is selected for the fitting process. The performance of the proposed method was verified by numerical simulation images and real images. Experimental results show that the proposed method is highly effective in handling displacement discontinuities.

关键词： Deformation measurement Digital image correlation sift algorithm Discontinuous deformation Reliable subset Displacement fitting

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