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.