Human authentication with finger textures based on image feature enhancement

Al-Nima, R. R. O., Dlay, Satnam, Chambers, Jonathon and Woo, Wai Lok (2016) Human authentication with finger textures based on image feature enhancement. In: ISP 2015 - 2nd IET International Conference on Intelligent Signal Processing 2015, 1st - 2nd December 2015, London, UK.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1049/cp.2015.1784

Abstract

The main goal of this paper is to authenticate people according to their finger textures. We propose to extract Finger Texture (FT) features of the four finger images (index, middle, ring and little) from a low resolution contactless hand image. Furthermore, we apply a new Image Feature Enhancement (IFE) method to enhance the FTs. The resulting feature image is segmented and a Probabilistic Neural Network (PNN) is employed as an intelligent classifier for recognition. Experimental results illustrate that the proposed approach has superior performance than recent published work. Moreover, the best IFE results were obtained with the Equal Error Rate (EER) equal to 4.07%.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Biometric authentication, Finger texture, Image enhancement, Inner knuckles, PNN
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 05 Apr 2019 13:32
Last Modified: 10 Oct 2019 20:16
URI: http://nrl.northumbria.ac.uk/id/eprint/38806

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