The two groups of popularly used texture analysis techniques for classification problems are the statistical and signal processing methods. In this paper, we propose to use a signal processing method, the Gabor filters to produce the feature images, and a statistical method, the covariance matrix to produce a set of features which show the statistical information of frequency domain. The experiments are conducted on 32 textures from the Brodatz texture dataset. The result that is obtained for the use of 24 Gabor filters to generate a 24 x 24 covariance matrix is 91.86%. The experiment results show that the use of Gabor filters as the feature image is better than the use of edge information and co-occurrence matrices.
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机译：用于分类问题的两种流行的纹理分析技术是统计和信号处理方法。在本文中，我们建议使用信号处理方法，Gabor滤波器来生成特征图像，并使用统计方法，协方差矩阵来生成一组可显示频域统计信息的特征。实验是对Brodatz纹理数据集中的32个纹理进行的。使用24个Gabor滤波器生成24 x 24协方差矩阵所获得的结果为91.86％。实验结果表明，使用Gabor滤波器作为特征图像比使用边缘信息和共现矩阵更好。
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