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Content Provider | IET Digital Library |
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Author | Huang, Wei Wu, Ling Da Song, Han Chen Wei, Ying Mei |
Abstract | The authors propose a robust descriptor based on BRIEF, called RBRIEF. Unlike the original BRIEF, the proposed descriptor is also robust to scale and in-plane rotation transformations. Furthermore, the authors use first derivative as sample function to do binary comparisons which has proven to be better compared against the function of intensity used in BRIEF. In the feature matching stage, the authors use Hamming distance to evaluate the descriptor similarity. As a result, the performance of the proposed descriptor outperforms SURF, BRIEF and ORB using standard benchmarks. In particular, the experiments demonstrate the proposed descriptor's superior performance in the presence of image blur, JPEG compression and light changes. Furthermore, the descriptor exhibits robust performance using only relatively few bits compared to other descriptors. |
Starting Page | 29 |
Ending Page | 35 |
Page Count | 7 |
ISSN | 17519632 |
Volume Number | 7 |
e-ISSN | 17519640 |
Issue Number | Issue 1, Feb (2013) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cvi/7/1 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2012.0087 |
Journal | IET Computer Vision |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Computer Vision And Image Processing Technique Data Compression Descriptor Similarity Hamming Distance Image And Video Coding Image Blur Image Coding Image Restoration In-plane Rotation Transformations JPEG Compression Light Changes Random Binary Comparisons RBRIEF Robust Descriptor Scale Rotation Transformations |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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