期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：1
出版社：IJCSI Press
摘要：This paper proposes a fingerprint features extraction using different levels. The hierarchical order at four different levels, namely, Level 1 (pattern), Level 2 (minutia points), Level 3 (pores and ridge contours), and Level 4 (oscillated pattern). The fingerprint feature extraction frequently take advantage of Level 4 features to assist in identification, Automated Fingerprint Identification Systems (AFIS) currently rely only on Level 1 and Level 2 features. In fact, the Federal Bureau of Investigation�s (FBI) standard of fingerprint resolution for AFIS is 500 pixels per inch (ppi), which is inadequate for capturing Level 3 features, such as pores. With the advances in fingerprint sensing technology, many sensors are now equipped with dual resolution (1,000 ppi) scanning capability. However, increasing the scan resolution alone does not necessarily provide any performance improvement in fingerprint matching, unless an extended feature set is utilized. As a result, a systematic analysis to determine how much performance gain one can achieve by introducing Level 4 features in AFIS is highly desired. We propose a hierarchical matching system that utilizes features at all the four levels extracted from 1,000-ppi fingerprints scans. Level 3 features, pores and ridge contours are automatically extracted using Gabor filters and wavelet transform and are locally matched using the Iterative Closest Point (ICP) algorithm and Level 4 features, oscillated pattern including curve scanned DCT to measure the recognition rate using k-nn classifier, Our analytical study conclude Level 4 features carry significant discriminatory information. The matching system when Level 4 features are employed in combination with Level 1 Level 2 and Level 3 features. This proposed method outperforms the others, particularly in recognition rate.
