Proceedings ArticleDOI
A touch-less fingerphoto recognition system for mobile hand-held devices
Kamlesh Tiwari,Phalguni Gupta +1 more
- pp 151-156
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TLDR
The proposed fingerphoto based human authentication system for mobile hand-held devices by using a non-conventional scale-invariant features eliminates the dependence over specifics scanners and has achieved CRR of 96.67% and EER of 3.33% which is better than any other system available in the literature.Abstract:
Fingerphoto is an image of a human finger obtained with the help of an ordinary camera. Its acquisition is convenient and does not require any particular biometric scanner. The high degree of freedom in finger positioning introduces challenges to its recognition. This paper proposes a fingerphoto based human authentication system for mobile hand-held devices by using a non-conventional scale-invariant features. The system utilizes built-in camera of the mobile devices to acquire biometric sample and therefore, eliminates the dependence over specifics scanners. It can successfully handle some of the issues like orientation, rotation and lack of registration at the time of matching. It has achieved CRR of 96.67% and EER of 3.33% which is better than any other system available in the literature.read more
Citations
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Contactless Fingerprint Recognition Based on Global Minutia Topology and Loose Genetic Algorithm
TL;DR: This paper proposes a robust contactless fingerprint recognition method based on global minutia topology and loose genetic algorithm, and proposes a new genetic algorithm (GA) named loose GA with new mutation and crossover operators.
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An overview of touchless 2D fingerprint recognition
TL;DR: In this article, the state-of-the-art in the field of touchless 2D fingerprint recognition at each stage of the recognition process is summarized and technical considerations and trade-offs of the presented methods along with open issues and challenges.
Proceedings ArticleDOI
Towards touchless pore fingerprint biometrics: A neural approach
TL;DR: This paper proposes the first innovative method in the literature able to extract Level 3 features, in particular sweat pores, from fingerprint images captured with a touchless acquisition using a commercial off-the-shelf camera.
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On Matching Finger-Selfies Using Deep Scattering Networks
TL;DR: An algorithm which comprises segmentation, enhancement, Deep Scattering Network based feature extraction, and Random Decision Forest to authenticate finger-selfies is proposed and results and comparison with existing algorithms show the efficacy of the proposed algorithm.
Posted Content
Mobile Touchless Fingerprint Recognition: Implementation, Performance and Usability Aspects.
TL;DR: An automated contactless fingerprint recognition system for smartphones is presented and a comparative usability study on both capturing device types indicates that the majority of subjects prefer the contactless capturing method.
References
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TL;DR: A novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
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TL;DR: This book addresses the void in biometrics research by inviting some of the prominent researchers in Biometrics to contribute chapters describing the fundamentals as well as the latest innovations in their respective areas of expertise.
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Preprocessing of a fingerprint image captured with a mobile camera
TL;DR: In this article, a preprocessing algorithm for fingerprint images captured with a mobile camera is proposed, which is different from images from conventional or touch-based sensors such as optical, capacitive, and thermal sensors.