Image Segmentation Based on Visual Saliency and Active Contour Model
Liu Min-bi · 2013
An effective object segmentation method is proposed which combines C-V model with saliency map,It first extract image saliency map,then gets the general contours of the object using the improved adaptive threshold segmentation,makes this contours as the initial curves of C-V model.When the background of the image is complex this method ensures the active contours evolve close to the object to obtain more accurate edge and reduce the number of iterations of the C-V model.The experimental results show that the segmentation accuracy and efficiency of the algorithm are better than the C-V model both for the images which have the obvious object.