This paper proposes a strategy for retrieving multi-texture images based on contour and texture segmentation. Firstly, the contour of each texture primitive is extracted from an image and its Fourier descriptor is calculated. Thus, the contours of the texture primitives in the original image are clustered according to these shape descriptors. Then Gabor wavelet transform is applied to extract the features of texture primitives for each group, so the image can be represented by a set of feature vectors in feature space. Finally, an improved and noise insensitive Hausdorff distance is used to calculate the distance between two feature vector sets. Furthermore, the retrieval of multi-texture images can be implemented. A large amount of experiments show that this method has higher retrieval precision, compared with the state-of-arts methods.