We introduce a novel skeleton extraction algorithm in binary and gray-scale images, based on the anisotropic heat diffusion analogy. We propose to diffuse image in the dominance of direction normal to the feature boundaries and also allow tangential diffusion to contribute slightly. The proposed anisotropic diffusion provides a high quality medial function in the image, since it removes noise and preserves prominent curvatures of the shape along the level-sets (skeleton locations). Then the skeleton strength map, which provides the likelihood to be a skeleton point, is obtained by computing the mean curvature of level-sets. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain thin and binary skeleton. Results indicate that this approach has advantages in handling noise in the image and in obtaining smooth shape skeleton because of the directional averaging inherent of our new anisotropic heat flow.