In recent years, automatic identification technique has been an emerging approach in real life. Especially, biometric authentication has drawn much attention. Due to its strong reliability, many modern approaches have been proposed by researchers and many biometric-related products have been developed. Fingerprint identification method has been researched and applied widely as a major technique in biometric domain. But the factors limiting the performance of fingerprint verification system mainly include fingerprint image quality, reliability of fingerprint minutiae, and the performance of fingerprint matching methods. Due to the uncontrollability of fingerprint image quality, the performance of whole fingerprint authentication system is mainly determined by the minutiae extraction algorithm and the fingerprint matching methods. Although fingerprint matching methods have been explored deeply, current matching algorithms can not still satisfy the real need completely. Most of current fingerprint matching schemes are based on minutiae. It is a well-known point pattern matching problem. This paper focuses on the problem and proposes several novel matching methods. We implemented them and demonstrated their effectiveness. Main innovative contributions to fingerprint matching in our paper are as follows: 1) Proposes a novel fingerprint matching algorithm based on triangle frameworks. The algorithm utilizes the distortion-tolerant triangle frameworks to deal with the nonlinear warping when placing fingers onto the sensor’s surface. It is noted that the normal fingerprint registration step is not necessary in the matching method. 2) Innovatively give a minutia representation scheme combing orientation field estimated form fingerprint images and apply it to fingerprint matching algorithm successfully. Due to the adoption of fingerprint global orientation information in the algorithm, our algorithm works better than those fingerprint matching methods only based on minutia information. 3) Proposes a novel minutia local structure which makes use of neighboring minutiae and global orientation fields. A new fingerprint matching technique based on our proposed structure is given. Because the matching algorithm uses more rich information including neighboring minutiae and orientation field, it gets better experimental results than some matching methods used only minutiae information or orientation information. 4) Firstly gives a new conception called “fingerprint cascading match” and proposes a general strategy for fingerprint cascading match. A specific fingerprint cascading matching algorithm is given. The algorithm can cascade several matching methods to attain a more effective matching approach. The experimental results show the better performance of cascading algorithm than single algorithm.
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