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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jun Ma Xiao jun Jing Bo Zhang Songlin Sun |
| Copyright Year | 2010 |
| Description | Author affiliation: School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China (Jun Ma; Xiao jun Jing; Bo Zhang; Songlin Sun) |
| Abstract | It is very important to detect the reference point effectively and accurately, especially in nonminutiae based fingerprint matching and fingerprint classification. In this paper, an effective algorithm based on block level for fingerprint reference point detection is proposed to simplify detection process and improve accuracy of the position of the point. The method is simple in the preprocessing and easy to implement. We used the Poincare Index on the block level, which is combined with the adaptive smoothing for getting a better orientation map and the directional consistency factor with the purpose of choosing the correct block. The proposed algorithm has been tested on fvc2002 and fvc2004 database. Experimental results show it is effective and practical. |
| Starting Page | 200 |
| Ending Page | 203 |
| File Size | 423061 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458455 |
| e-ISBN | 9781424458486 |
| DOI | 10.1109/ICACC.2010.5487210 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-03-27 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Smoothing methods Poincare Index Crops reference point Fingerprint recognition directional consistency factor Covariance matrix orientation field Sun Matched filters adaptive smoothing Databases Image matching Feature extraction Testing |
| Content Type | Text |
| Resource Type | Article |
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