A Novel Fingerprint Image Preprocessing Algorithm

Ming Fu; Jun  Huang; Jun Xu

doi:10.4028/www.scientific.net/AMM.347-350.2528

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350A Novel Fingerprint Image Preprocessing Algorithm

A Novel Fingerprint Image Preprocessing Algorithm

Abstract:

Based on analyzing and experimenting a large number of the existing fingerprint image preprocessing algorithm, this paper presents a novel high-quality fingerprint image preprocessing algorithm. Taking full account of the inherent characteristics of the fingerprint image, the algorithm arranges overall features and local detail. The experiments show that it is a simple, efficient algorithm which can improve the quality of the fingerprint image, and lay a good foundation for the subsequent processing.

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

Pages:

2528-2532

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.347-350.2528

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Online since:

August 2013

Authors:

Ming Fu, Jun Huang, Jun Xu

Keywords:

Fingerprint Recognition, Preprocessing, Thinning

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References

[1] Lowe. D. G, Distinctive image features from scale invariant key points, International Journal of Computer Vision, 60(2), 2004 , pp.91-110.

DOI: 10.1023/b:visi.0000029664.99615.94

Google Scholar

[2] Xi ping. Luo, Jie. Tian, Image Enhancement and Minutia Matching Algorithms in Automated Fingerprint Identification System, Journal of Software, 13(5), 2002, pp.946-955.

Google Scholar

[3] Yuan Yuan. Zhou, Cheng. Zhang, Algorithms for fingerprint image preprocessing, Computer Applications, 24(9), Sept. 2004, pp.34-36.

Google Scholar

[4] Xiao Dong. Yang, Xin Bao. Ning, Fingerprint Image Preprocessing Technique and Feature Extraction Algorithm, journal of nanjing university(natural science), 42(4), July . 2006, pp.351-361.

Google Scholar

[5] Xin e. You, Fingerprint Information Extraction Research Based on the Orientation and Dynamic Threshold, Computer Simulation , 29(8), Aug . 2012, pp.253-255.

Google Scholar

[6] Chun Lei. Ji, Wei. Feng, Dynamic Threshold with Hole Padding Algorithm for Fingerprint Image Binarization, Computer Simulation , 28(7), July. 2011, pp.258-261.

Google Scholar

[7] Wei. Yang, Ke. Guo, An Efficient Index Thinning Algorithm of Fingerprint Image Based on Eight Neighbourhood Points., Journal Of SiChuan University Of Science & Engineering (Natural Science Edition), 21(2), Apr. 2008, pp.61-63.

Google Scholar

[8] Ying. Chen, Realization of automatic fingerprint identification system, Journal of zhejiang University of Science and Technology, 24(4), Aug. 2012, pp.303-309.

Google Scholar