Features Image Matchingof SUＲF and ＲANSAC
Aiming at the problem of long running time and low matching accuracy in image matching process， random sample consensus ( ＲANSAC) algorithm is used to optimize the speed-up of robust features ( SUＲF) optimization algorithm. As a result，an adaptable algorithm is proposed to optimize image matching....
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2018-02-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1490 |
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| _version_ | 1849225170265309184 |
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| author | WANG Wei-bing BAI Xiao-ling XU Qian |
| author_facet | WANG Wei-bing BAI Xiao-ling XU Qian |
| author_sort | WANG Wei-bing |
| collection | DOAJ |
| description | Aiming at the problem of long running time and low matching accuracy in image matching process，
random sample consensus ( ＲANSAC) algorithm is used to optimize the speed-up of robust features ( SUＲF)
optimization algorithm. As a result，an adaptable algorithm is proposed to optimize image matching. Firstly，the
SUＲF operator is used for feature detection and feature description. Then the neighbor algorithm is used to prematch
the feature points. Finally，the random sampling consistency ( ＲANSAC) algorithm is used to optimize the
matching results. The scale invariant feature transform ( SIFT) algorithm，SUＲF algorithm，and the proposed
optimization algorithm are compared in the same experimental environment. Compared with the SIFT algorithm and
the SUＲF algorithm，the optimization algorithm reduces the number of matching point pairs to 38 and 18 pairs，
excluding mismatched points，improving the matching accuracy，and reducing the running time of the algorithm.
|
| format | Article |
| id | doaj-art-3fe01a1ee9ab45c8836aa4e966c981aa |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2018-02-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-3fe01a1ee9ab45c8836aa4e966c981aa2025-08-25T05:54:40ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832018-02-01230111712110.15938/j.jhust.2018.01.021Features Image Matchingof SUＲF and ＲANSACWANG Wei-bing0BAI Xiao-ling1XU Qian2School of Computer Science and Technology，Harbin University of Science and Technology，Harbin 150080，ChinaSchool of Computer Science and Technology，Harbin University of Science and Technology，Harbin 150080，ChinaHeilongjiang Electric Power Ltd. Harbin District，Harbin 150000，ChinaAiming at the problem of long running time and low matching accuracy in image matching process， random sample consensus ( ＲANSAC) algorithm is used to optimize the speed-up of robust features ( SUＲF) optimization algorithm. As a result，an adaptable algorithm is proposed to optimize image matching. Firstly，the SUＲF operator is used for feature detection and feature description. Then the neighbor algorithm is used to prematch the feature points. Finally，the random sampling consistency ( ＲANSAC) algorithm is used to optimize the matching results. The scale invariant feature transform ( SIFT) algorithm，SUＲF algorithm，and the proposed optimization algorithm are compared in the same experimental environment. Compared with the SIFT algorithm and the SUＲF algorithm，the optimization algorithm reduces the number of matching point pairs to 38 and 18 pairs， excluding mismatched points，improving the matching accuracy，and reducing the running time of the algorithm. https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1490feature matchingspeed up robust featuresrandom sample consensus |
| spellingShingle | WANG Wei-bing BAI Xiao-ling XU Qian Features Image Matchingof SUＲF and ＲANSAC Journal of Harbin University of Science and Technology feature matching speed up robust features random sample consensus |
| title | Features Image Matchingof SUＲF and ＲANSAC |
| title_full | Features Image Matchingof SUＲF and ＲANSAC |
| title_fullStr | Features Image Matchingof SUＲF and ＲANSAC |
| title_full_unstemmed | Features Image Matchingof SUＲF and ＲANSAC |
| title_short | Features Image Matchingof SUＲF and ＲANSAC |
| title_sort | features image matchingof surf and ransac |
| topic | feature matching speed up robust features random sample consensus |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1490 |
| work_keys_str_mv | AT wangweibing featuresimagematchingofsurfandransac AT baixiaoling featuresimagematchingofsurfandransac AT xuqian featuresimagematchingofsurfandransac |