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| Content Provider | IET Digital Library |
|---|---|
| Author | Wang, Ke Zhu, Ningyu Cheng, Yao Li, Ruifeng Zhou, Tianxiang Long, Xuexiong |
| Abstract | Feature matching has been frequently applied in computer vision and pattern recognition. In this paper, the authors propose a fast feature matching algorithm for vector-based feature. Their algorithm searches r-nearest neighborhood clusters for the query point after a k-means clustering, which shows higher efficiency in three aspects. First, it does not reformat the data into a complex tree, so it shortens the construction time twice. Second, their algorithm adopts the r-nearest searching strategy to increase the probability to contain the exact nearest neighbor (NN) and take this NN as the global one, which can accelerate the searching speed by 170 times. Third, they set up a matching rule with a variant distance threshold to eliminate wrong matches. Their algorithm has been tested on large SIFT databases with different scales and compared with two widely applied algorithms, priority search km-tree and random kd-tree. The results show that their algorithm outperforms both algorithms in terms of speed up over linear search, and consumes less time than km-tree. Finally, they carry out the CFI test based on ISKLRS database using their algorithm. The test results show that their algorithm can greatly improve the recognition speed without affecting the recognition rate. |
| Starting Page | 198 |
| Ending Page | 207 |
| Page Count | 10 |
| Volume Number | 3 |
| e-ISSN | 24682322 |
| Issue Number | Issue 4, Dec (2018) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/trit/3/4 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1041 |
| Journal | CAAI Transactions on Intelligence Technology |
| Publisher | The Institution of Engineering and Technology Chongqing University of Technology Chinese Association for Artificial Intelligence |
| Publisher Date | 2018-10-22 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Subject Keyword | Algorithm Searches CFI Algorithm Combinatorial Mathematics Complex Tree Computer Vision Computer Vision And Image Processing Technique Fast Feature Matching Algorithm Feature Extraction Image Matching Image Recognition Linear Search Matching Rule Mathematics Nearest Neighbourhood Clusters Nearest Searching Strategy Pattern Clustering Pattern Recognition Priority Search Km-tree Random Kd-tree Search Problem Searching Point Searching Speed Trees Vector-based Feature Wrong Matches |
| Content Type | Text |
| Resource Type | Article |
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