Abstract
Fingerprint recognition is one of the research hotspots of biometrics techniques. And fingerprint classification and matching are key parts in an automated fingerprint recognition system. The traditional fingerprint recognition systems have such disadvantages as high computation complexity, low speed, low recognition rate to uncompleted or defiled fingerprints, and not robust. In this paper, we propose a novel fingerprint classification and matching method based on synergetic pattern recognition, which emphasizes global features of fingerprint. With lots of artificial fingerprint samples, the results show that the proposed method is effective, fast and robust. In the end, experimental results are analyzed and a synergetic fingerprint recognition system is introduced.
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