光电工程, 2007, 34 (3): 98, 网络出版: 2007-11-14  

基于谱直方图表示和支持向量机的纹理分类

Texture classification using spectral histogram representation and support vector machines
作者单位
电子科技大学,电子工程学院,四川,成都,610054
摘要
在纹理分类中采用谱直方图表示(SHR),每个图像窗表示一个包含滤波后图像直方图的特征向量,而直方图是图像谱表示的连接桥梁.在滤波器选择算法之前,结合每个图像分块和滤波器的独立谱表示和直方图,可以获得更加低层的局部特征.最后,时所有独立滤波器采用滤波器选择算法来得到所需的少量滤波器.为了保证分类的可靠性,选择高斯径向基函数(RBF)进行谱直方图表示,采用支持向量机(SVMs)作为分类函数.对本文方法和其它两种方法:Gabor滤波和独立成分分析(ICA)进行了纹理分类和脸部识别的比较实验.实验结果表明,本文方法具有更高的分类准确性,也证明了SVMs优秀的泛化能力.
Abstract
When applying Spectral Histogram Representation (SHR) for texture classification, each image window is represented as a feature vector consisting of histograms of filtered images, and the histograms are concatenated to form the spectral representation for the image. Independent spectral representations and histograms for each image patch and each filter are combined to yield only very low-level local feature before the algorithm of filter selection. Finally, a filter selection algorithm is applied to select a small number of filters from all the independent filters. To improve classification reliability, aGaussian Radial Basis Function (RBF) is chosen on the Spectral Histogram Representation and the Support Vector Machines (SVMs) is used as classifying function. Comparison experiments between the proposed method and the other two methods:Gabor filtering and Independent Component Analysis (ICA) in texture classification and face recognition are performed.Experimental results demonstrate that higher categorization accuracy can be achieved with the proposed method, and theexcellence of the generalization performance of SVMs can be confirmed.

黄启宏, 刘钊. 基于谱直方图表示和支持向量机的纹理分类[J]. 光电工程, 2007, 34(3): 98. 黄启宏, 刘钊. Texture classification using spectral histogram representation and support vector machines[J]. Opto-Electronic Engineering, 2007, 34(3): 98.

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