Currently, image retrieval is based on images color, texture, shape and other characteristics to match. The speed and accuracy of retrieval can not meet the needs of users. Image retrieval based on scale invariant feature transform (SIFT) is carried on. But there are too many feature points and dimensions, which has an impact on real-time retrieve. Locality preserving projections (LPP) in SIFT is used to reduce dimension in order to reduce number of feature points. The enhanced approximate nearest neighbor method is used to improve the accuracy of the match. A secondary judgment mechanism is added, when it is matching. If they are possible match points, handshake confirmation is executed. Experimental results show that based on the experimental verification of 20 images in image library, the improved SIFT algorithm improves the timeliness and matching rate of image retrieval. So that, it can be well applied in image retrieval.