Semantics-based image retrieval by region saliency (2002)
| Venue: | in Proceeding International Conference on Image and Video Retrieval (LNCS 2382 |
| Citations: | 3 - 0 self |
BibTeX
@INPROCEEDINGS{Wang02semantics-basedimage,
author = {Wei Wang and Yuqing Song and Aidong Zhang},
title = {Semantics-based image retrieval by region saliency},
booktitle = {in Proceeding International Conference on Image and Video Retrieval (LNCS 2382},
year = {2002},
pages = {29--37}
}
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Abstract
Abstract. We propose a new approach for semantics-based image retrieval. We use color-texture classification to generate the codebook which is used to segment images into regions. The content of a region is characterized by its self-saliency and the lower-level features of the region, including color and texture. The context of regions in an image describes their relationships, which are related to their relative-saliencies. High-level (semantics-based) querying and query-by-example are supported on the basis of the content and context of image regions. The experimental results demonstrate the effectiveness of our approach. 1
Citations
| 1123 | Color indexing - Swain, Ballard - 1991 |
| 146 | Comparing images using color coherence vectors - Pass, Zabih, et al. - 1996 |
| 37 | Automatic identification of perceptually important regions in an image - Osberger, Maeder - 1998 |
| 20 | Keyblock: An approach for content-based image retrieval - Zhu, Zhang, et al. - 2000 |
| 20 | Data and Model-Driven Selection Using Color Regions - Syeda-Mahmood - 1997 |
| 8 | Semantics retrieval by content and context of image regions - Wang, Song, et al. - 2002 |
| 5 | On measuring low-level saliency in photographic images - Luo, Singhal - 2000 |
