Combining document representations for known-item search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Scene-based image retrieval by transitive matching
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Pill-ID: Matching and retrieval of drug pill images
Pattern Recognition Letters
Index model for image retrieval using SIFT distortion
International Journal of Intelligent Information and Database Systems
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Tattoo images on human body have been routinely collected and used in law enforcement to assist in suspect and victim identification. However, the current practice of matching tattoos is based on keywords. Assigning keywords to individual tattoo images is both tedious and subjective. We have developed a content-based image retrieval system for a tattoo image database. The system automatically extracts image features based on the Scale Invariant Feature Transform (SIFT). Side information, i.e., body location of tattoos and tattoo classes, is utilized to improve the retrieval time and retrieval accuracy. Geometrical constraints are also introduced in SIFT keypoint matching to reduce false retrievals. Experimental results on 1,000 queries against an operational database of 63,593 tattoo images show a rank-20 accuracy of 94.2%; the average matching time per query is 2.9 sec. on Intel Core 2, 2.66 GHz, 3 GB RAM processor.