首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Evolutionary segmentation of texture image using genetic algorithms towards automatic decision of optimum number of segmentation areas
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Evolutionary segmentation of texture image using genetic algorithms towards automatic decision of optimum number of segmentation areas

机译:使用遗传算法对纹理图像进行进化分割,以自动确定最佳分割区域数

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摘要

Segmentation of an image composed of different kinds of texture fields has difficulty in an exact discrimination of the texture fields and a decision of the optimum number of segmentation areas in an image when the image contains similar and or unstationary texture fields. In this paper we formulate the segmentation problem upon such images as an optimization problem and adopt evolutionary strategy of genetic algorithms for the clustering of small regions in a feature space. The purpose of this paper is to demonstrate the efficiency of genetic algorithms to the texture segmentation and to develop the automatic texture segmentation method.
机译:当图像包含相似的和/或不稳定的纹理场时,对由不同种类的纹理场组成的图像进行分割难以准确区分纹理场,并且难以确定图像中分割区的最佳数量。在本文中,我们将图像的分割问题称为优化问题,并采用遗传算法的进化策略对特征空间中的小区域进行聚类。本文的目的是证明遗传算法对纹理分割的有效性,并开发自动纹理分割方法。

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