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Robust weighted Keypoint matching algorithm for image retrieval

Authors
Jeong D.-M.Kim J.-H.Lee Y.-W.Kim B.-G.
Issue Date
Dec-2018
Publisher
Association for Computing Machinery
Keywords
Edge information; Image retrieval; Keypoint extraction; Keypoint matching; Robust keypoint
Citation
ACM International Conference Proceeding Series, pp.145 - 149
Journal Title
ACM International Conference Proceeding Series
Start Page
145
End Page
149
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4131
DOI
10.1145/3301506.3301513
Abstract
The important factor which controls the accuracy of image matching process is a keypoint extraction. This paper describes a new weighted keypoint matching algorithm for improving the performance of image retrieval. The basic concept is to use the edge information. First, we compute the Scale Invariant Feature Transform (SIFT) features as keypoints from an input image. Also, the edge image is obtained for updating the ranking of the extracted keypoints. With the obtained edge map, we assign weights to keypoints where they correspond on the edge map. Finally the ranking of keypoints is re-ordered and Top-32 keypoints are selected based on the RootSIFT to matching process. Through the experiments, we verify that the proposed algorithm achieves 2.4% of more accuracy than the original SIFT detector when various distortions exist.
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