An approach for image retrieval based on visual saliency

Considering the gap between low-level image features and the high-level semantic concept in content-based image retrieval (CBIR), a new approach is proposed for image retrieval based on visual saliency, by analyzing the human visual perception process. Visual information is introduced as the new feature which reflects high-level semantic concept objectively. First, the visual saliency model for image retrieval is established. The saliency features of intensity, color and texture are calculated. Second, integrated global saliency map is synthesized and its statistic histogram is used as a new feature in image retrieval. Finally, the similarity of color images is computed by combining the color feature and the histogram of integrated saliency map. Results of experiments show that our approach improves retrieval precision and recall when compared with the classical color feature approach.