Anisotropic diffusion for object segmentation

Abstract

We describe a method for object segmentation that uses a modified version of the anisotropic diffusion algorithm. The original anisotropic diffusion is performed in the original image, and it is not suitable for texture or noisy images. Our method achieves accurate object detection by using anisotropic diffusion in another 2D space whose size is the same as the processed image. This space is called energy space. The idea is simple. The energy will center on the pixels in the energy space corresponding to the edge pixels of the real image. It can simplify the original overly complex schemes to save computation time. The authors also propose a novel edge linking method by edge directional vector based on the energy space. By experimental evidence, our method can increase the noise tolerance.