An AntiGeometric Diffusion Classification Based Image Binarization Method
HUANG Qian1, WU Yuan2, YIN JunXun1
1.School of Electronic and Information Engineering, South China University of Technology, Guangzhou 5106402. School of Informatics, University of Bradford, BRADFORD BD7 1DP UK
Abstract It is difficult to extract objects from background due to the uneven and complex background information. In this paper, a binarization method is developed, which is based on the antigeometric diffusion, a special form of the anisotropic diffusion. The antigeometric diffusion method is used to blur and diffuse the edge of images as much as possible, and thus many threshold surfaces are formed. Each pixel is classified during the diffusion process according to the developed classification criterions. Finally, a postprocessing approach is proposed to extract the object from background. The numerical experimental results show that the presented method is robust to the noise restriction. Furthermore, the results for handling Xray images of casting products with uneven background by the presented method are given.
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2008, Vol. 21 
