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The usefulness of an image database depends on whether the image of interest can be easily located. Feature extraction is a crucial step of image retrieval. The well known SIFT descriptor is a keypoint based image feature. It can be used to robustly find the same objects in different images, i.e., achieve the object recognition task. However, it is not effective on the image retrieval task, i.e., finding images with similar content. To improve the SIFT algorithm, we propose a robust image retrieval algorithm based on the integration of keypoints and edges information. Our approach is robust to translation, rotation and partial occlusion of the object. Experimental results indicate that the proposed algorithm is effective and outperforms the SIFT algorithm.