Adaptive Morphology Active Contour for Image Segmentation

we proposed a regional active contours with morphological approximation. Incorporating local adaptive neighborhood image information by performing adapted spatial and intensity morphology opening and closing using semi-flat general adaptive neighborhood structuring elements. Integrating a general adaptive in local neighborhood information caused robustness of morphological active contour model to inhomogeneity, also solving the minimized energy function by morphological approximation increase stability and speed of contour evolution. Thus a general spatially and intensity adapted information combining global morphological active contour without edges are generalized that is robust to noise, inhomogeneity and no need to re-initialization.