Residual orientation modeling for fingerprint enhancement and singular point detection
| Autor: | Wei-Yun Yau, Vutipong Areekul, Suksan Jirachaweng, Zujun Hou |
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| Rok vydání: | 2011 |
| Předmět: |
Biometrics
Computer science Image quality Data_MISCELLANEOUS Image processing Singular point of a curve Residual Singularity Artificial Intelligence Fingerprint ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION Computer Science::Multimedia Computer vision Legendre polynomials Computer Science::Cryptography and Security business.industry Orientation (computer vision) Pattern recognition Fingerprint recognition Data_GENERAL Computer Science::Computer Vision and Pattern Recognition Signal Processing Computer Vision and Pattern Recognition Artificial intelligence business Software |
| Zdroj: | Pattern Recognition. 44:431-442 |
| ISSN: | 0031-3203 |
| DOI: | 10.1016/j.patcog.2010.08.019 |
| Popis: | This paper presents a novel method for fingerprint orientation modeling, which executes in two phases. Firstly, the orientation field is reconstructed using a lower order Legendre polynomial to capture the global orientation pattern in the fingerprint structure. Then the preliminary model around the region with presence of fingerprint singularities is dynamically refined using a higher order Legendre polynomial. The singular region is automatically detected through the analysis on the orientation residual field between the original orientation field and the orientation model. The method does not require any prior knowledge on the fingerprint structure. To validate the performance, the method has been applied to fingerprint image enhancement, fingerprint singularity detection and fingerprint recognition using the FVC 2004 data sets. Compared with the recently published Legendre polynomial model, the proposed method attains higher accuracy in fingerprint singularity detection, lower error rates in fingerprint matching. |
| Databáze: | OpenAIRE |
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