A novel algorithm for image retrieval based on prominent interest points is presented. The algorithm consists of three steps: prominent interest points detection,feature description based on prominent interest points and similarity measurement,image is filtered by a self-adaptive filter,then prominent interest points are extracted;prominent interest points are regarded as clues,and annular color histogram is designed,which takes not only the local color feature into consideration but also the space distribution information of prominent interest points;the similarities are measured by the distance of annular color histograms. With robustness to rotation and translation,the algorithm avoids shortcoming of losing the location information in color histogram. Experimental results show that this algorithm is efficient for image retrieval.