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检索条件"主题词=SIFT Algorithm"

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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...

引用

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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3D Reconstruction of Surface Based on Binocular Vision

3D Reconstruction of Surface Based on Binocular Vision

引用

6th International Symposium on Precision Mechanical Measurements (ISPMM)

作者： Hu, Xiaoping Peng, Tao Xie, Ke Hunan Univ Sci & Technol Hunan Prov Key Lab Hlth Maintenance Mech Equipmen Xiangtan 411201 Hunan Peoples R China

ISBN: (纸本)9780819497925

This paper proposes a feasible program of 3D curve surface reconstruction based on the method of binocular stereo vision system which is composed of two industrial CCD cameras. On the basis of bipolar linear constraints, the method gets information modules to match the 3D curve surface feature at sub-pixel level by the sift algorithm so that the reconstruction of 3D stereo structure can be realized. Then, through the combination of the acquired feature vectors with 2D image to affine the curve surface, the feature extraction and the recognition progress can be realized by iteration. Finally, a 3D depth map can be produced. This method can help improve the robustness of the stereo matching and get a better 3D reconstruction in a simple way with low cost.

关键词： 3D Reconstruction binocular vision sift algorithm robustness

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A New Registration Method Base on Improved Sobel and sift algorithms

A New Registration Method Base on Improved Sobel and SIFT Al...

引用

2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)

作者： Qiu-Ju Yang Xue-Mei Xiao College of Computer Science Sichuan University

In order to remove the unstable edge response points of the image registration using original sift algorithm and get more stable matching results in image registration, a new registration method based on improved Sobel algorithm and sift algorithm is proposed. The new method firstly detects out key points of image by original sift algorithm, then uses the features for image registration and finds out the edge responses of the matching point with the improved Sobel algorithm at last. It would remove some registration points if their coordinates are equal to the edge point. The rest registration points have different coordinates will be kept. The experimental results show that the improved registration algorithm can effectively remove the edge response points, further improve the accuracy of the registration result and display better stability than the traditional registration algorithm.

关键词： sift algorithm key points Sobel algorithm Image registration edge detection

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A sift Feature Matching algorithm Based on Semi-Variance Function

A SIFT Feature Matching Algorithm Based on Semi-Variance Fun...

引用

2012 International Conference on Biomaterial and Bioengineering(ICBB 2012)

作者： Feng Tian Yubo Yan School of Computer Science Shenyang Aerospace University

For solving the low matching efficiency problem due to high dimension of eigenvector in sift, a sift feature matching algorithm based on semi-variance function is proposed. For each feature point in image sift feature point zone, m beams are generated by using the position of the feature point as center and the orientation of the feature point as start direction. The image semi-variance function value of each beam, which is treated as sift value of eigenvector descriptor, is used in the algorithm aiming at reducing the dimension of eigenvector and improving image matching efficiency. The experiment result shows that the matching rate of this algorithm is higher, the matching time of this algorithm is less.

关键词： sift algorithm Feature Matching Semi-Variance Function Feature Descriptor

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Study on Application of Scale Invariant Feature Transform algorithm on Automated Geometric Correction of Remote Sensing Images

Study on Application of Scale Invariant Feature Transform Al...

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第六届国际计算机与计算技术在农业中的应用研讨会

作者： Hui Deng Limin Wang Jia Liu Dandan Li Zhongxin Chen Qingbo Zhou Key Lab.of Resources Remote Sensing & Digital Agriculture Ministry of Agriculture Institute of Agriculture Resources and Regional Planning Chinese Academy of Agricultural Sciences

In recent years,data collected from remote sensing satellite and aerophotography have been showing a geometric sequence increase.A method of Scale Invariant Feature Transform(sift) algorithm could be employed for the automatic geometric fine *** method could avoid the impact of the rotation and zooming of template matching during the image matching process,and it can also save the labor during the image processing *** on the sift algorithm,this paper proposes a two-step method,which firstly conducts coarse match on feature points,and then further conducts fine correction on the coarsely matched feature points by using the least squares *** result indicates that,this method is an effective automatic matching method for remote sensing images.

关键词： remote sensing image automatic geometric correction sift algorithm least squares

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Research on Image Registration and Mosaic Based on Vector Similarity Matching Principle

Research on Image Registration and Mosaic Based on Vector Si...

引用

5th International Symposium on Computational Intelligence and Design (ISCID)

作者： Qin, Jia Yang, Jianfeng Xue, Bin Bu, Fan Chinese Acad Sci Xian Inst Opt & Precis Mech Key Lab Spectrum Imaging Technol Xian Peoples R China

ISBN: (纸本)9780769548111

Scale invariant feature transform (sift) is a better corner extraction algorithm, but there are still mismatching problems in the feature matching step. A new matching principle based on vector similarity is proposed and then it is compared with traditional matching principle. Firstly, the matching feature points are detected by the new principle. Mismatching points are further removed by using the mutual mapping theory. Secondly, transformation matrix is calculated by random sample consensus (RANSAC). Furthermore, the matrix is optimized by Levenberg-Marquardt algorithm (L-M). Lastly, image mosaic is realized by image fusion. Experimental results indicate that compared with traditional matching principle, new matching principle has improved matching accuracy. It is able to apply new principle to image registration and image mosaic.

关键词： image mosaic sift algorithm feature matching vector similarity mutual mapping

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An algorithm for Image Match Propagation

An Algorithm for Image Match Propagation

引用

International Conference on Industrial Control and Electronics Engineering (ICICEE)

作者： Liu, Rong He, Liang Lu, Kaiyun E China Inst Technol Dept Surveying Fuzhou 344000 Jiangxi Peoples R China

ISBN: (纸本)9780769547923

Stereo matching is an important part of 3D reconstruction. This paper proposes an improved match propagation algorithm. Firstly, the feature points are extracted and matched by sift algorithm then they are used as seed points for the image match propagation in neighborhood. Secondly, these dense correspondences are resampled to quasi-dense correspo-ndences. Finally, the mismatched points and outliers are eliminated by epipolar constraint. Experiments show that this improved algorithm can be applied in the similar structure of images with great change of depth

关键词： sift algorithm propagation epipolar constraint quasi-dense matching

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A Barcode Recognition Based on Multiform algorithms

A Barcode Recognition Based on Multiform Algorithms

引用

4th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

作者： Zhang, Yunfei Lu, Bo Su, Limin Beijing Union Univ Coll Informat Being Peoples R China

ISBN: (纸本)9780769547213

This paper takes EAN-13 barcode as an example to introduce multiform algorithms about automatic recognition. The algorithms consist of sift algorithm and the algorithm of optimized similar border distance measurement. Respective experimented on the same barcode, we got the result about the two algorithms. We acquired their characteristics and the fields which they are suited in. By experiment, all of them have high rate of recognition, low requirement for images and high calculating speed. So, they can meet the needs of responsiveness and automation well.

关键词： barcode sift algorithm similar border image matching

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Research on Image Registration and Mosaic Based on Vector Similarity Matching Principle

Research on Image Registration and Mosaic Based on Vector Si...

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2012 Fifth International Symposium on Computational Intelligence and Design [第五届计算智能与设计国际会议 ISCID 2012]

作者： Fan Bu Jia Qin Bin Xue Jianfeng Yang Key Laboratory of Spectrum Imaging Technology Xi'an Institute of Optics and Precision Mechanics CA Key Laboratory of Spectrum Imaging Technology Xi'an Institute of Optics and Precision Mechanics CA

Scale invariant feature transform (sift) is a better corner extraction algorithm, but there are still mismatching problems in the feature matching step. A new matching principle based on vector similarity is proposed and then it is compared with traditional matching principle. Firstly, the matching feature points are detected by the new principle. Mismatching points are further removed by using the mutual mapping theory. Secondly, transformation matrix is calculated by random sample consensus (RANSAC). Furthermore, the matrix is optimized by LevenbergMarquardt algorithm (L-M). Lastly, image mosaic is realized by image fusion. Experimental results indicate that compared with traditional matching principle, new matching principle has improved matching accuracy. It is able to apply new principle to image registration and image mosaic.

关键词： image mosaic sift algorithm feature matching vector similarity mutual mapping

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A New sift-Based Camera Calibration Method for Hybrid Dual-Camera

A New SIFT-Based Camera Calibration Method for Hybrid Dual-C...

引用

International Conference on Informatics Engineering and Information Science (ICIEIS 2011)

作者： Low, Yi-Qian Lee, Sze-Wei Goi, Bok-Min Ng, Mow-Song Univ Tunku Abdul Rahman Fac Sci & Engn Kuala Lumpur Malaysia

ISBN: (纸本)9783642254529;9783642254536

Camera networks, consisting of various types of camera systems. play an important role in security surveillance system. This paper presents a new calibration method for hybrid multi-camera system;particularly, a video surveillance system with a static camera and a dynamic camera which is used for environment-monitoring and security purpose. The first static wide angle camera covers the complete scene, whereas the second dynamic camera, Pan-Tilt-Zoom (PTZ) camera provides multi-view-angle and multi-resolution images of the complete scene. The new proposed calibration method is based on Lowe's Scale invariant Feature Transform (sift) algorithm and keypoints are selected based on the measurement of their stability. To improve the accuracy and robustness, a simple noise (unwanted keypoints) filtering technique using trigonometry theorem has also been adopted in the proposed system. From the obtained experimental results, it is shown that great improvement, in term of the determination and detection rate (from 55.71% to 94.87%) in camera networks calibration, has been achieved.

关键词： Camera Calibration sift algorithm Mutli-camera System

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