Skeletonization by Gradient Diffusion and Regularization

Abstract

This paper describes a skeletonization process for grayscale or color images which uses the diffusion of the image gradient vectors. We propose to diffuse the native gradients of the color images to obtain the skeleton of the main contrasted objects. Contrary to a distance transform or thinning based skeleton, the gradient vectors diffusion is a straightforward, simple, and efficient approach to compute the skeleton, which requires no complex parameters or predefined criteria and no prior image binarization. In comparison to other approaches based on potential field functions, our method does not require the segmentation of the objects or the precise localization of their contours. Our method is very simple to implement and can be applied to natural noisy color images. Some results on real color and grayscale images are reported.