A novel method for image retrieval based on color and spatial distribution features of interest points was presented.The content of one image is looked as an aggregation of some interest points.Firstly,we present a wavelet-based detector,which uses the space-tree property of the transform coefficients to estimate the interest points.Secondly,to provide geometric invariant image matching,annular color histogram and spatial cohesion based on interest points are presented to describe image features.Finally,the weighted feature distance is used to discriminate the similarity between two images.The annular color histogram and spatial cohesion are used to make this method remain invariant to the image's scale,rotation and translation.A series of experiments based on an image database consisting of 1000 images are performed to confirm the effectiveness of our method.In these experiments,our method provides more accurate and efficient retrieval performance comparing with other interest points-based retrieval method.