纹理分割是图象处理的基本问题之一．针对广泛的纹理图象，需要一个高效、鲁棒的分割方法，因此提出了一种基于纹理基元的纹理图象分割算法．首先，以Harr小波为变换工具，得到具有方向性的纹理子图象；然后给出了一种新的纹理基元提取方法，并在此基础上，应用统计方法和矢量场，对纹理区域进行由粗到细的分割．通过这种方法不仅可以对纹理图象进行分割，还可以对同一区域的纹理结构进行描述，从而有利于在这种分割方法基础上，进行更高层次的图象处理．

Texture segmentation is one of fundamental problems in image processing. An efficient and robust method is needed for various texture samples. Consequently, this paper presents a texton-based algorithm of texture image segmentation. At first, Harr wavelet is utilized as a transform tool so that texture subimages of different directions are produced. And then, we use double threshold technology to get edges and propose a new method to extract textons of four directions. Thereafter, textons are simplified to one dimension vector and reduced to twelve kinds. At last, Statistics and vector field are applied respectively in order to separate texture images from coarse to fine. The algorithm is simple and effective for a wide of textures. Through this way, texture images are not only separated, but also texture structure can be described, which is useful for high-level image processing tasks.