Classification method for colored natural textures using Gabor filtering

Leena Lepistö, I. Kunttu, J. Autio, A. Visa
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引用次数: 34

Abstract

The common methods of texture analysis are based on the gray levels of the texture image. However, the use of color information improves the classification accuracy of colored textures. In the classification of non-homogenous natural textures, human perception of texture and color are important. Therefore, the color space and texture analysis method should be selected to correspond to human vision. We present an effective method for the classification of colored natural textures. The natural textures are often non-homogeneous and directional, which makes them difficult to classify. In our method, multiresolution Gabor filtering is applied to the color components of the texture image in HSI color space. Using this method, the colored texture images can be classified in multiple scales and orientations. Experimental results show that the use of color information improves the classification of natural textures.
基于Gabor滤波的彩色自然纹理分类方法
常用的纹理分析方法是基于纹理图像的灰度值。然而,颜色信息的使用提高了彩色纹理的分类精度。在非均质自然纹理的分类中,人对纹理和颜色的感知是很重要的。因此,色彩空间和纹理分析方法的选择应符合人的视觉。提出了一种有效的彩色自然纹理分类方法。自然纹理通常是非均匀和定向的,这使得它们难以分类。该方法在HSI颜色空间中对纹理图像的颜色分量进行多分辨率Gabor滤波。利用该方法可以对彩色纹理图像进行多尺度、多方向的分类。实验结果表明,颜色信息的使用改善了自然纹理的分类。
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