An approach for image segmentation based on visual saliency is proposed in this paper. First low-level visual features of the image are extracted. Local saliency

global saliency and rarity saliency are computed for each feature map to get the feature conspicuity maps. Then these conspicuity maps are integrated to generate the saliency map. The saliency map is segmented using a threshold and a binary mask map is obtained. Finally the foreground and background of the original image are separated by adding the binary map to the original image. The proposed model has been tested on many natural images. Experimental results show that the proposed approach is valid and the segmentation results are consistent with human visual system.