关键词: 水平集, 向量CV模型, 图像分割, 形状先验

Abstract: Chan et al proposes the vector CV model to solve the problem that the traditional CV model cannot segment the vector images, but it has a bad effect on the complex images that have noise or occlusions, so this paper proposes the vector CV model combining shape prior. Its energy function is mainly composed of shape prior information term and image area information term and distance regularization term. When the evolved active contour and shape prior have similar positions, the contour stops evolution. According to the affine transformation of shape, using a gradient descent algorithm for template to match makes the algorithm more flexible. The model has good segmentation result for the noise and clutter image.

Key words: level set, vector CV model, image segmentation, shape prior