Unconstrained and contactless hand geometry biometrics.

Sensors
Alberto de-Santos-SierraJavier Guerra-Casanova

Abstract

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.

References

Jul 13, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Erdem YörükJérôme Darbon
Aug 12, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Ajay Kumar, David Zhang
Nov 2, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jose M PalomaresAlberto Prieto
Apr 22, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Vivek KanhangadDavid Zhang

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Citations

Aug 26, 2014·TheScientificWorldJournal·Chorng-Shiuh KoongChien-Chao Tseng
May 18, 2017·Frontiers in Bioengineering and Biotechnology·Vrajeshri PatelRamana Vinjamuri

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Methods Mentioned

BETA
feature extraction

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