Research on SIFT Image Matching Based on MLESAC Algorithm
| Title | Research on SIFT Image Matching Based on MLESAC Algorithm |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Deng, Lijin, Piao, Yan, Liu, Shuo |
| Conference Name | Proceedings of the 2Nd International Conference on Digital Signal Processing |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-6402-7 |
| Keywords | composability, compressive sampling, Cyber physical system, cyber physical systems, image matching, matching accuracy, MLESAC algorithm, privacy, pubcrawl, resilience, Resiliency, SIFT algorithm |
| Abstract | 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. |
| URL | https://dl.acm.org/citation.cfm?doid=3193025.3193059 |
| DOI | 10.1145/3193025.3193059 |
| Citation Key | deng_research_2018 |