基于内容的图象检索是近年来的研究热点，为此提出了一种自动区分均质纹理和非均质纹理图象，并对这两类图象分别进行检索的算法.算法首先从图象离散小波变换的低频子带提取一定的颜色和纹理特征用于模糊聚类，将图象的低频子带分割为一定的区域 ;然后根据分割的结果将图象自动语义分类为均质纹理或者非均质纹理图象 ;最后对均质纹理和非均质纹理图象分别提取不同的特征矢量，并按照一定的相似度准则检索图象.实验结果表明，该算法具有良好的均质纹理和非均质纹理图象分类和检索性能.

Content-based Image retrieval techniques are the research focuses in recent years. A texture and non-texture images retrieval algorithm is proposed in this paper. Firstly, we perform wavelet transform on the images; secondly we perform fuzzy clustering in the LL subband of the images according to the color and texture features; thirdly we can judge that the images are texture or non-texture by using the region segmentation, and extract different features, we extract the global energy features for texture images and the local energy features for non-texture images; then, according to the different similarity acriterion, we can get the similarity of texture images and non-texture images. For non-texture images, we must first get region similarity and relation between the regions of two images, and then we can get similarity between images. For texture images, we can directly get image similarity from the global energy features. The algorithm is confirmed by the test that can get good classify and retrieval performance.