Feature Weighted Active Contours for Image Segmentation
A novel external energy construction for active contours is proposed in this paper. In contrast to the standard approach of using linear filtering to smooth the external energies and to avoid noise, we define feature weighted active contours for extracting features of interest without distortion. The advantages of this innovation are demonstrated by examples and comparisons with Gaussian filtered external energy. Compared to the linear filtering approach, the feature weighted active contours yield lower root mean squared errors of contour position and improve upon the ability to capture fine details in noisy images