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In this chapter, we introduce a new binarization method of gray level images. We first extract skeleton curves from Canny edge image. Second, a Skeleton Strength Map (SSM) is calculated from Euclidean distance transform. Starting from the boundary edges, the distance transform is firstly computed and its gradient vector field is calculated. After that, the isotropic diffusion is performed on the gradient vector field and the SSM is computed from the diffused vector field. It has two advantages that make it useful for skeletonization: 1) the SSM serves as the form of the likelihood of a pixel being a skeleton point: the value at pixels of the skeleton is large while at pixels that are away from the center of object, the SSM value decays very fast; 2) By computing the SSM from the distance transform, a parameterized noise smoothing is obtained. Then, skeleton curves are classified into foreground and background …