Robust feature extraction and salvage schemes for finger texture based biometrics

Al-Nima, Raid, Dlay, Satnam, Al-Sumaidaee, Saadoon, Woo, Wai Lok and Chambers, Jonathon (2017) Robust feature extraction and salvage schemes for finger texture based biometrics. IET Biometrics, 6 (2). pp. 43-52. ISSN 2047-4938

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In this study, an efficient human authentication method is proposed which utilises finger texture (FT) patterns. This method consists of two essential contributions: a robust and automatic finger extraction method to isolate the fingers from the hand images; and a new feature extraction method based on an enhanced local line binary pattern (ELLBP). To overcome poorly imaged regions of the FTs, a method is suggested to salvage missing feature elements by exploiting the information embedded within the trained probabilistic neural network used to perform classification. Three databases have been applied in this study: PolyU3D2D, IIT Delhi and spectral 460 from Multi-spectral CASIA images. Experimental studies show that the best result was achieved by using ELLBP feature extraction. Furthermore, the salvaging approach proved effective in increasing the verification rate.

Item Type: Article
Uncontrolled Keywords: feature extraction, fingerprint identification, image classification, image texture, neural nets, probability
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 03 Apr 2019 15:25
Last Modified: 10 Oct 2019 20:34

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