In this paper we propose a content based image retrieval method for diagnosis aid in diabetic retinopathy. We characterize images without extracting significant features, and use histograms obtained from the compressed images in JPEG-2000 wavelet scheme to build signatures. The research is carried out by calculating signature distances between the query and database images. A weighted distance between histograms is used. Retrieval efficiency is given for different standard types of JPEG-2000 wavelets, and for different values of histogram weights. A classified diabetic retinopathy image database is built allowing algorithms tests. On this image database, results are promising: the retrieval efficiency is higher than 70% for some lesion types