Fast image matching algorithm based on affine invariants

被引:0
|
作者
张毅 [1 ,2 ]
卢凯 [1 ,2 ]
高颖慧 [3 ]
机构
[1] National Laboratory for Parallel and Distributed Processing(National University of Defense Technology)
[2] College of Computer,National University of Defense Technology
[3] College of Electronic Science and Engineering,National University of Defense Technology
基金
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词
affine invariants; image matching; extended centroid; robustness; performance;
D O I
暂无
中图分类号
TP391.41 [];
学科分类号
080203 ;
摘要
Feature-based image matching algorithms play an indispensable role in automatic target recognition(ATR).In this work,a fast image matching algorithm(FIMA)is proposed which utilizes the geometry feature of extended centroid(EC)to build affine invariants.Based on affine invariants of the length ratio of two parallel line segments,FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features,and increases the feature diversity of different targets,thus reducing misjudgment rate during recognizing targets.However,it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation.An advanced FIMA is designed to cope with these problems.Experiments prove that the proposed algorithms have better robustness for Gaussian noise,gray-scale change,contrast change,illumination and small three-dimensional rotation.Compared with the latest fast image matching algorithms based on geometry features,FIMA reaches the speedup of approximate 1.75 times.Thus,FIMA would be more suitable for actual ATR applications.
引用
收藏
页码:1907 / 1918
页数:12
相关论文
共 50 条
  • [1] Fast image matching algorithm based on affine invariants
    Zhang Yi
    Lu Kai
    Gao Ying-hui
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2014, 21 (05) : 1907 - 1918
  • [2] Fast image matching algorithm based on affine invariants
    Yi Zhang
    Kai Lu
    Ying-hui Gao
    Journal of Central South University, 2014, 21 : 1907 - 1918
  • [3] Fast image matching algorithm with approximate affine and scale invariance
    Yue J.
    Gao S.-L.
    Li F.-M.
    Cai N.-B.
    Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2020, 28 (10): : 2349 - 2359
  • [4] Fast Affine Invariant Image Matching
    Rodriguez, Mariano
    Delon, Julie
    Morel, Jean-Michel
    IMAGE PROCESSING ON LINE, 2018, 8 : 251 - 281
  • [5] Fast Line Segment Matching Based on Point-Line Affine Invariants and Pairwise Constraints
    Zhang, Haowei
    Zhang, Zhihe
    Yan, Zhaoyan
    Li, Yan
    FOURTEENTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING, ICGIP 2022, 2022, 12705
  • [6] An improved algorithm for fast image matching based on SURF
    Cui J.
    Sun C.
    Li Y.
    Fu L.
    Wang P.
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2022, 43 (08): : 47 - 53
  • [7] Fast Image Matching Algorithm Based on Projection Characteristics
    Zhou Lijuan
    Yue Xiaobo
    Zhou Lijun
    THIRD INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2011), 2011, 8009
  • [8] A Fast Image Matching Algorithm Based on Key Points
    Wang Huilin
    Wang Ying
    An Ru
    Yan Peng
    REMOTE SENSING OF THE ENVIRONMENT: 18TH NATIONAL SYMPOSIUM ON REMOTE SENSING OF CHINA, 2014, 9158
  • [9] Image Matching Algorithm Based on Improved FAST and RANSAC
    Yang, Qiongnan
    Qiu, Chenguang
    Wu, Litao
    Chen, Jianjun
    2021 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2021), 2021, : 142 - 147
  • [10] Fast image correlative matching based on genetic algorithm
    Zhu, H
    Zhao, YG
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 1999, 18 (02) : 145 - 150