纹理图象分割的分形方法研究

Texture Image Segmentation Based on the Fractal Dimension

在分形维数的基础上研究了将其用于纹理分割的方法。采用差分盒维数（ＤＢＣ）方法和一种改进的边缘保持算法计算象素点的分形维数ＦＤ，基于原始图象的方向性差分和多重分形的概念提取出一组特征，并将Ｋｏｈｏｎｅｎ的ＳＯＦＭ网用于对得到的图象特征矢量进行分类，得到了较好的纹理图象分割效果。

Deals with the problem of recognizing and segmenting textures in images based on the fractal dimension (FD). Differential box counting (DBC) method and a modified edge preserving approach are used to estimate the FD. Six features are based on the original image, the horizontally differential image, the vertically differential image, two diagonally differential image, and the multi fractal dimension of order two. Kohonen′s SOFM net is adopted to cluster the feature vectors, and the segmentation results show the efficiency of the technique. The result is compared with feature smoothing and K means approach.