| Title | Fingerprint indexing based on composite set of reduced SIFT features |
| Authors | Shuai, Xin Zhang, Chao Hao, Pengwei |
| Affiliation | Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing 100871, China Department of Computer Science, Queen Mary University of London, London E1 4NS, United Kingdom |
| Issue Date | 2008 |
| Citation | 2008 19th International Conference on Pattern Recognition, ICPR 2008.Tampa, FL, United states. |
| Abstract | Most of current fingerprint indexing schemes utilize features based on global textures and minutiae structures. To extend the existing technology of feature extraction, this paper proposes a new fingerprint indexing and retrieval scheme using scale invariant feature transformation (SIFT), which has been widely used in generic image retrieval. With slight loss in effectiveness, we reduce the number of features generated from one fingerprint for efficiency. To cope with the uncertainty of acquisition (e.g. partialness, distortion), we use a composite set of features to form multiple impressions for the fingerprint representation. In the index construction phase, the use of locality-sensitive hashing (LSH) allows us to perform similarity queries by only examining a small fraction of the database. Experiments on database FVC2000 and FVC2002 show the effectiveness of our proposed scheme. ? 2008 IEEE. |
| URI | http://hdl.handle.net/20.500.11897/327566 |
| Indexed | EI |
| Appears in Collections: | 机器感知与智能教育部重点实验室 |
