A Fast and Efficient Wavelet-Based Active Contour Method

In this paper, we propose a new method for fast and effective image segmentation using snakes (active contours). This method incorporates the active contour models with the wavelet transform features using directional edges in high and low frequency content sub-images. The proposed method takes advantages of these features to improve the boundary attraction process in active contour models. It also enhances the speed of image segmentation process by using a multi-scale approach. The analytical results show the efficiency of the proposed method in extraction of objects in images while performing the image segmentation at a higher speed compared to previously proposed active contour models.