Abstract
Local features of images have been widely used in image retrieval, however, the cost is so heavy. To address this issue, a superpixel-based approach for image retrieval is proposed. We first extract the image structure that preserves the main information and removes the redundant information from the image by smoothing and oversegment a smoothed image into a certain number of superpixels. We then extract the positive candidate superpixels by combining superpixels with local descriptors. Finally, we compute the similarity of two images by analyzing two sets of positive candidate superpixels. Experiments on dataset PQ7 demonstrate the performance of the proposed approach.
Original language | English |
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Title of host publication | Proceedings of 2017 International Conference on Video and Image Processing, ICVIP 2017 |
Publisher | Association for Computing Machinery |
Pages | 156-160 |
Number of pages | 5 |
ISBN (Electronic) | 9781450353830 |
DOIs | |
Publication status | Published - 27 Dec 2017 |
Event | 2017 International Conference on Video and Image Processing, ICVIP 2017 - Singapore, Singapore Duration: 27 Dec 2017 → 29 Dec 2017 |
Conference
Conference | 2017 International Conference on Video and Image Processing, ICVIP 2017 |
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Country/Territory | Singapore |
City | Singapore |
Period | 27/12/17 → 29/12/17 |
Keywords
- Image retrieval
- Key-point
- Smoothing
- Superpixel
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software