Image Segmentation Based on Visual Attention Mechanism

A new approach for image segmentation based on visual attention mechanism is proposed. Motivated biologically, this approach simulates the bottom-up human visual selective attention mechanism, extracts early vision features of the image and constructs the saliency map. Multiple image features such as intensity, color and orientation in multiple scales are extracted to get some feature maps. The phase spectra of the feature maps are analyzed in frequency spectrum domain. Then the corresponding feature saliency maps are constructed in spatial domain and theses feature saliency maps are combined to an integrated saliency map. According to the saliency map, the salient regions in an image are detected. The image is segmented by seperating the salient regions and the backgroud. This approach has been tested on natrual images. Experiment results and quantitative and qualitative analysis have been presented in this paper. The proposed results are consistent with human manual segmentation results. This proposed approach is effective in computational speed, segmentation result and it is robust to noise.