A novel region-based image retrieval algorithm using selective visual attention model

Authors:
Songhe Feng;De Xu;Xu Yang;Aimin Wu
Affiliations:
Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China;Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China;Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China;Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China
Venue:
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2005

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Abstract

Selective Visual Attention Model (SVAM) plays an important role in region-based image retrieval. In this paper, a robust and accurate method for salient region detection is proposed which integrates SVAM and image segmentation. After that, the concept of salient region adjacency graphs (SRAGs) is introduced for image retrieval. The whole process consists of three levels. First in the pixel-level, the salient value of each pixel is calculated using an improved spatial-based attention model. Then in the region-level, the salient region detection method is presented. Furthermore, in the scene-level, salient region adjacency graphs (SRAGs) are introduced to represent the salient groups in the image, which take the salient regions as root nodes. Finally, the constructed SRAGs are used for image retrieval. Experiments show that the proposed method works well.