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

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.

[1]  Xiaojun Qi,et al.  A novel fusion approach to content-based image retrieval , 2005, Pattern Recognit..

[2]  Zheru Chi,et al.  Attention-driven image interpretation with application to image retrieval , 2006, Pattern Recognit..

[3]  Huang Ying,et al.  Multi-Resolution Template Match Using Wavelet Transform , 2000 .

[4]  Chen-Kuei Yang.  Content-based color quantization and texture extraction for image indexing , 2006 .

[5]  Fred Stentiford,et al.  Attention-based similarity , 2007, Pattern Recognit..

[6]  James Lee Hafner,et al.  Efficient Color Histogram Indexing for Quadratic Form Distance Functions , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Oge Marques,et al.  An Attention-Driven Model for Grouping Similar Images with Image Retrieval Applications , 2007, EURASIP J. Adv. Signal Process..

[8]  Pietro Perona,et al.  Is bottom-up attention useful for object recognition? , 2004, CVPR 2004.

[9]  Oge Marques,et al.  Using visual attention to extract regions of interest in the context of image retrieval , 2006, ACM-SE 44.

[10]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[11]  Jitendra Malik,et al.  Color- and texture-based image segmentation using EM and its application to content-based image retrieval , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  Jitendra Malik,et al.  Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..