Title: Multi-level fingerprint continuous classification for large-scale fingerprint database using fractal analysis

Authors: Yunfei Zhong; Xiaoqi Peng

Addresses: School of Information Science and Engineering, Central South University, Changsha, 410083, China; School of Packaging Materials and Engineering, Hunan University of Technology, Zhuzhou, 412007, China ' School of Information Science and Engineering, Central South University, Changsha, 410083, China

Abstract: A three-level classification method using fractal analysis was proposed to improve the speed, accuracy, and robustness of an automated recognition system for a large-scale fingerprint database. Low-quality fingerprints were first eliminated via an assessment algorithm with a multi-level progressive discriminant factor. Next, three-level classification was done for fingerprints with acceptable quality. The fingerprints were sorted into six categories according to fingerprint types. Classification was made based on the number of ridge lines between the singular points of each fingerprint. Categorisation was done in terms of the fractal dimensions of the stable-quality region of each fingerprint image. With the second and third levels of classification, continuous classification and redundancy retrieval could be achieved. The experimental results using the NIST-4 fingerprints database established that the proposed method has various advantages, including fast retrieval speeds, strong adaptability, and great robustness, making it particularly suitable for automated classification and recognition matching for large-scale databases.

Keywords: box dimension; fingerprint recognition; multi-level continuous classification; redundancy retrieval; large-scale databases; fingerprint classification; fingerprint databases; fractal analysis; biometrics; automated recognition; ridge lines; fingerprints.

DOI: 10.1504/IJBM.2016.077829

International Journal of Biometrics, 2016 Vol.8 No.2, pp.115 - 133

Received: 04 Aug 2015
Accepted: 08 Apr 2016
Published online: 16 Jul 2016 *

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