Research on SIFT Image Matching Based on MLESAC Algorithm

被引：0
|
作者：
Deng, Lijin [1 ]
Piao, Yan [1 ]
Liu, Shuo [2 ]
机构：
[1] Changchun Univ Sci & Tech, Changchun, Jilin, Peoples R China
[2] CETC52, Hangzhou, Zhejiang, Peoples R China
来源：
2018 2ND INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (ICDSP 2018) | 2018年
关键词：
Image matching; SIFT algorithm; MLESAC algorithm; matching accuracy;
D O I：
10.1145/3193025.3193059
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The difference of sensor devices and the camera position offset will lead the geometric differences of the matching images. The traditional SIFT image matching algorithm has a large number of incorrect matching point pairs and the matching accuracy is low during the process of image matching. In order to solve this problem, a SIFT image matching based on Maximum Likelihood Estimation Sample Consensus (MLESAC) algorithm is proposed. Compared with the traditional SIFT feature matching algorithm, SURF feature matching algorithm and RANSAC feature matching algorithm, the proposed algorithm can effectively remove the false matching feature point pairs during the image matching process. Experimental results show that the proposed algorithm has higher matching accuracy and faster matching efficiency.
引用
收藏
页码：17 / 21
页数：5
相关论文
共 50 条
  • [31] An Improved Harris-SIFT Algorithm for Image Matching
    Cao, Yu
    Pang, Bo
    Liu, Xin
    Shi, Yan-li
    [J]. ADVANCED HYBRID INFORMATION PROCESSING, 2018, 219 : 56 - 64
  • [32] A Novel Image Retrieval Algorithm Based on ROI by Using SIFT Feature Matching
    Wang, Zhuozheng
    Jia, Kebin
    Liu, Pengyu
    [J]. 2008 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND INFORMATION TECHNOLOGY, PROCEEDINGS, 2008, : 338 - 341
  • [33] A novel SAR image precise-matching method based on SIFT algorithm
    Yan, Wenwen
    Li, Bin
    Yang, Dekun
    Tian, Jinwen
    Yu, Qiong
    [J]. MIPPR 2013: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS, 2013, 8921
  • [34] Image matching based on the adaptive redundant keypoint elimination method in the SIFT algorithm
    Hossein-Nejad, Zahra
    Agahi, Hamed
    Mahmoodzadeh, Azar
    [J]. PATTERN ANALYSIS AND APPLICATIONS, 2021, 24 (02) : 669 - 683
  • [35] Image matching based on the adaptive redundant keypoint elimination method in the SIFT algorithm
    Zahra Hossein-Nejad
    Hamed Agahi
    Azar Mahmoodzadeh
    [J]. Pattern Analysis and Applications, 2021, 24 : 669 - 683
  • [36] Image Matching Based on LBP and SIFT Descriptor
    Kabbai, Leila
    Azaza, Aymen
    Abdellaoui, Mehrez
    Douik, Ali
    [J]. 2015 IEEE 12TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD), 2015,
  • [37] Robust image matching based on the information of SIFT
    Dou, Jianfang
    Qin, Qin
    Tu, Zimei
    [J]. OPTIK, 2018, 171 : 850 - 861
  • [38] An Image Matching Method Based on SIFT Feature
    Shi, Zhaoming
    Geng, Boying
    Wu, Zhonghong
    Dong, Yinwen
    [J]. PROGRESS IN CIVIL ENGINEERING, PTS 1-4, 2012, 170-173 : 2855 - 2859
  • [39] Image matching with an improved descriptor based on SIFT
    Hu, Xuemei
    Ding, Yan
    [J]. SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONICS AND INFORMATION ENGINEERING, 2017, 10322
  • [40] VIDEO OBJECT MATCHING BASED ON SIFT ALGORITHM
    Hu, Xuelong
    Tang, Yingcheng
    Zhang, Zhenghua
    [J]. 2008 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND SIGNAL PROCESSING, VOLS 1 AND 2, 2007, : 412 - 415
12345