A Content-Based Image Retrieval system using Visual Attention

Semantic gap, difference between visual features and semantic annotations, is an important problem of Content-Based Image Retrieval (CBIR) systems. In this study, a new Content-Based Image Retrieval system is proposed by using Visual Attention which is a part of human visual system. In the proposed work, the region of interests are extracted by using Itti-Koch visual attention model. The attention values, obtained from the saliency maps are used to define a new similarity matching method. Successful results are obtained compared to traditional region-based retrieval systems.