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首页> 外文会议>Machine Vision, 2009. ICMV '09 >Gabor Filter Parameters Optimization for Texture Classification Based on Genetic Algorithm
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Gabor Filter Parameters Optimization for Texture Classification Based on Genetic Algorithm

机译：基于遗传算法的纹理分类Gabor滤波器参数优化

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摘要

Despite Gabor filtering has emerged as one of the leading techniques for texture classification, a unifying approach to its adoption has not emerged yet. As it is true for Gabor filter bank, the design of a filter bank consists of the selection of a proper set of values for the filter parameters. In this paper, it is intended to find a set of Gabor filter bank parameters optimized for the performance of texture classification system. The application method is suggested to compute Gabor filter parameters based on Genetic Algorithm (GA). The parameters are optimized according to each group of textures. We tested the proposed method with several texture images using a standard database. The experimental results demonstrate the effectiveness of proposed approach as the overall success is about 97.5%.
机译：尽管Gabor滤波已成为纹理分类的主要技术之一，但尚未出现采用这种方法的统一方法。对于Gabor滤波器组来说确实如此，滤波器组的设计包括为滤波器参数选择一组适当的值。本文旨在找到一组针对纹理分类系统性能优化的Gabor滤波器组参数。提出了一种基于遗传算法的Gabor滤波器参数计算方法。根据每组纹理优化参数。我们使用标准数据库用几个纹理图像测试了该方法。实验结果证明了该方法的有效性，因为总体成功率为97.5％。

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