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A novel content-based image retrieval approach based on attention-driven model

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4 Author(s)
Ying-Hua Lu ; Northeast Normal Univ., Changchun ; Xiao-Hua Zhang ; Jun Kong ; Xue-Feng Wang

Visual attention plays a vital role for humans to understand a scene by intuitively emphasizing some focused objects, and recent work in the model of visual attention has demonstrated that a purely bottom-up approach to identify salient regions within an image can be successfully applied to diverse problems. Being aware of this, a novel approach of extracting objects of interest (OOIs) based on attention-driven in an image is proposed. In this approach, the modified Itti-Koch model (M-Itti-Koch) of visual attention is used to find salient peaks, and then if these peaks overlap with regions generated by EM (expectation-maximization) algorithm, we proceed to extract attentive object around that point. Only these objects are considered for the next step, feature extraction and match. This attention-driven model used for CBIR provides a promising performance, as compared with some current peer systems in the literature.

Published in:

Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on  (Volume:2 )

Date of Conference:

2-4 Nov. 2007