Locating salient edges for CBIR based on visual attention model

Authors:
Feng Songhe;Xu De
Affiliations:
Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China;Dept. of Computer Science & Technology, Beijing Jiaotong Univ., Beijing, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

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Abstract

Visual attention model was usually used for salient region detection. However, little work has been employed to use the model for salient edge extraction. Since edge information is also important element to represent the semantic content of an image, in this paper, attention model is extended for salient edges detection. In our approach, an improved saliency map computing algorithm is employed first. Then, based on the saliency map, a novel and efficient salient edges detection method is introduced. Moreover, the concept of salient edge histogram descriptors (SEHDs) is proposed for image similarity comparison. Experiments show that the proposed algorithm works well.