Texture Segmentation Based On Moment And BP Neural Network

The most important technology in texture segmentation is texture features extraction. Moment, as a feature descriptor is employed to extract the texture features efficiently. Considered the aspects of image description, information redundancy and noise sensitivity, Zernike moment is more better than Geometrical moment and Legendre moment. But these kinds of moments can only extract global features from images, Wavelet moment solves this problem. In this paper, Zernike moment and Wavelet moment is used to extract texture feature to accomplish segmentation.First, a texture segmentation algorithm based on Zernike moment and BP neural network is presented, in which the feature extraction is divided into two steps: first, the Zernike moments in small local windows of the image are computed; second, a nonlinear transducer is used to map the moments to texture features and these features are used to construct feature vectors served as input data of the clustering algorithm. Then a BP neural network is employed to perform segmentation. Compared the segmentation result based on Legendre moment, the result based on Zernike moment is better.Then the problem of selecting Zernike moment order and windows size is discussed, and such conclusions are gained: 1. If high Zernike moment order is used, good segmentation result is gotten, but the more higher order is sensitive to noise, thus the segmentation result becomes bad. 2. The first window size is determined by the texture itself character, textures with large texture tokens require large window sizes whereas textures with finer texture tokens require smaller window sizes; The second window is should set as large as possible to enhance the continuity of the segmentation result.We also presented the segmentation algorithm based on Wavelet moment and BP neural network. According to the conception of wavelet transition and moment, we introduced Wavelet moment. In our experiment, we mainly used two kind of Wavelet moment—B Spline moment and Haar moment. Besides these we presented an algorithm of feature selection. Compared the segmentation results of texture pairs which have little difference between them, the results based on B-Spline moment are better than that of Haar moment, than that of Zernike moment.