Name
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3177404.3177428 | PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON VIDEO AND IMAGE PROCESSING (ICVIP 2017) |
Keywords | Field | DocType |
Image retrieval, smoothing, superpixel, key-point | Pattern recognition,Computer science,Image retrieval,Smoothing,Artificial intelligence,Image structure | Conference |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhixiang He | 1 | 13 | 3.34 |
| xiaoli sun | 2 | 32 | 7.54 |
| Chenhui Li | 3 | 27 | 11.16 |
| George Baciu | 4 | 409 | 56.17 |
| Yushi Li | 5 | 2 | 2.05 |