An Effective Image Retrieval Technique Based on Color Perception

In content-based image retrieval (CBIR), color is the most intuitive image features and it is widely used. But The current color feature can describe the semantics of the whole image effectively, but does not reflect characteristics of the color salience objects in an image. For the purpose of giving prominence to the color characteristics of salience objects, this paper proposes a new color feature descriptor based on color visual perception model. By analyzing the human color visual perception process, the color perception model is proposed at first. This model integrates the intensity, the color contrast and self saliency, sparsity and centricity saliency to describe human color visual perception of the image. Then, the new color feature descriptor is calculated by weighting the significant bit-plane histograms with color perception map. Finally, similarity measure is presented for the new color feature. Experiment results show that the proposed color feature is more accurate and efficient in retrieving images with user-interested color objects. Compared with the other three retrieval methods, the proposed technique improves the retrieval accuracy effectively.