检索结果-内蒙古大学图书馆

11th International Conference on Digital Image Processing (ICDIP)

作者： Li, Xiangyu Lei, Tianjie Zhao, Chun Huang, Jintao Yuan, Man Wang, Jiabao China Inst Water Resources & Hydropower Res IWHR Beijing 100038 Peoples R China North China Univ Water Resources & Elect Power NC Zhengzhou 450000 Peoples R China

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630765

In order to solve the problems of poor stability and multiple mismatching points in image registration, most scholars have used Random Sample Consensus (RANSAC) algorithm to optimize the matching algorithm. However, because of the randomness of the RANSAC algorithm itself, the matching algorithm has poor stability, low registration efficiency and poor robustness. To solve this problem, an improved SIFT (Scale-invariant feature transform) image registration optimization algorithm based on prosac (Progressive Sampling Consensus) was proposed. The experimental results showed that the proposed image registration optimization algorithm could effectively solve the problems of error matching and low efficiency in the process of image matching. Using the same image to test, the average correct registration rate of the traditional RANSAC improved SIFT algorithm was 82%, and the average running time was 36 seconds. The average correct registration rate of the SIFT image registration algorithm based on prosac improved SIFT image registration algorithm was 86.67%, the average running time was 26.51 seconds, and the running efficiency was increased by 36%. Therefore, the improved SIFT image registration algorithm based on prosac has higher robustness, can meet the needs of fast image mosaic, and has broad application prospects.

关键词： Image stitching SIFT algorithm RANSAC algorithm prosac algorithm

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Research on Improved Image Registration algorithm Based on prosac algorithm

Research on Improved Image Registration Algorithm Based on P...

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2019第十一届数字图像处理国际会议

作者： Xiangyu Li Tianjie Lei Chun Zhao Jintao Huang Man Yuan Jiabao Wang China Institute of Water Resources and Hydropower Research(IWHR) North China University of Water Resources and Electric Power(NCWU)

In order to solve the problems of poor stability and multiple mismatching points in image registration,most scholars have used Random Sample Consensus(RANSAC) algorithm to optimize the matching ***,because of the randomness of the RANSAC algorithm itself,the matching algorithm has poor stability,low registration efficiency and poor *** solve this problem,an improved SIFT(Scale-invariant feature transform) image registration optimization algorithm based on prosac(Progressive Sampling Consensus) was *** experimental results showed that the proposed image registration optimization algorithm could effectively solve the problems of error matching and low efficiency in the process of image *** the same image to test,the average correct registration rate of the traditional RANSAC improved SIFT algorithm was 82%,and the average running time was 36 *** average correct registration rate of the SIFT image registration algorithm based on prosac improved SIFT image registration algorithm was 86.67%,the average running time was 26.51 seconds,and the running efficiency was increased by 36%.Therefore,the improved SIFT image registration algorithm based on prosac has higher robustness,can meet the needs of fast image mosaic,and has broad application prospects.

关键词： Image stitching SIFT algorithm RANSAC algorithm prosac algorithm

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Research on Workpiece Image Mosaic Technology of Groove Cutting Robot

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021年第9期46卷 9065-9082页

作者： Chu, Hui-Hui Xue, Bin Li, Ning Qingdao Binhai Univ Coll Mech & Elect Engn Dev Zone Qingdao 425 West Jialingjiang Rd Qingdao 266555 Shandong Peoples R China

Aiming at the requirement of obtaining the panorama of the worktable in the automatic cutting system of workpiece groove based on machine vision, an image registration algorithm based on SIFT and improved prosac is proposed. First, SIFT algorithm is used for feature detection and feature description. Then, the bidirectional matching and cosine similarity method are used for rough matching of feature points. Finally, an improved prosac algorithm is proposed, which purifies the matching points and calculates the image transformation matrix. In image fusion, the weighted average method is used to fuse the overlapping parts of the image to obtain a whole image of the cutting platform. Experimental results show that the algorithm in this paper has been improved in terms of matching accuracy and time-consuming compared with several classical algorithms.

关键词： Automatic groove cutting Image registration algorithm SIFT feature extraction prosac algorithm

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Automatic Seamless Image Mosaic Method Based on SIFT Features 2

Automatic Seamless Image Mosaic Method Based on SIFT Feature...

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2nd International Conference on Photonics and Optical Engineering (icPOE)

作者： Liu, Meiying Wen, Desheng Chinese Acad Sci Xian Inst Opt & Precis Mech 17 Xinxi Rd Xian 710119 Peoples R China Univ Chinese Acad Sci 19 A Yuquan Rd Beijing 100049 Peoples R China

ISBN: (纸本)9781510610132;9781510610149

An automatic seamless image mosaic method based on SIFT features is proposed. First a scale-invariant feature extracting algorithm SIFT is used for feature extraction and matching, which gains sub-pixel precision for features extraction. Then, the transforming matrix H is computed with improved prosac algorithm, compared with RANSAC algorithm, the calculate efficiency is advanced, and the number of the inliers are more. Then the transforming matrix H is purify with LM algorithm. And finally image mosaic is completed with smoothing algorithm. The method implements automatically and avoids the disadvantages of traditional image mosaic method under different scale and illumination conditions. Experimental results show the image mosaic effect is wonderful and the algorithm is stable very much. It is high valuable in practice.

关键词： image mosaic SIFT features prosac algorithm transforming matrix

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An Improved GMS Image Feature Matching algorithm Based on BEBLID Descriptor 2

An Improved GMS Image Feature Matching Algorithm Based on BE...

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2nd International Conference on Optics and Image Processing (ICOIP)

作者： Peng, Shuaishuai Yan, Qicheng Wu, Tong Hohai Univ Sch Comp & Informat Nanjing 211100 Peoples R China

ISBN: (纸本)9781510657274;9781510657267

Aiming at the shortage of matching accuracy of ORB algorithm in image matching stage and the poor robustness of GMS algorithm under repeated texture conditions, this paper proposed an improved GMS image feature matching algorithm based on BEBLID descriptor. This algorithm firstly uses the ORB algorithm for image feature point extraction, secondly describes the feature points with BEBLID descriptor, after that discards false matching pair preliminarily by brute force matching. In order to improve the matching accuracy of the algorithm, two algorithms GMS and prosac are combined on this basis to obtain better matching pairs. The experimental results show that the algorithm has uniform extraction of feature points and high matching accuracy for different image feature matching, and its correct rate is improved by 10.97 percentage points to the GMS algorithm, which can meet the demand of large parallax image matching and improve the accuracy and efficiency of target acquisition in vision tasks.

关键词： ORB BEBLID Feature matching GMS algorithm prosac algorithm

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Automatic Seamless Image Mosaic Method Based on SIFT Features

Automatic Seamless Image Mosaic Method Based on SIFT Feature...

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2016年第二届光子学与光学工程国际会议暨第八届西部光子学会议

作者： Meiying Liu d.wen XI'AN INSTITUTE OF OPTICS AND PRECISION MECHANICS(China)

An automatic seamless image mosaic method based on SIFT features is *** a scale-invariant feature extracting algorithm SIFT is used for feature extraction and matching,which gains sub-pixel precision for features ***,the transforming matrix H is computed with improved prosac algorithm,compared with RANSAC algorithm,the calculate efficiency is advanced,and the number of the inliers are *** the transforming matrix H is purify with LM *** finally image mosaic is completed with smoothing *** method implements automatically and avoids the disadvantages of traditional image mosaic method under different scale and illumination *** results show the image mosaic effect is wonderful and the algorithm is stable very *** is high valuable in practice.

关键词： image mosaic SIFT features prosac algorithm transforming matrix

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