Hand Veins Feature Extraction using DTCNNs

Suleyman Malki, Y Fuqiang, Lambert Spaanenburg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper we study the potential of Cellular Neural Networks implemented on a Field-Programmable Gate Array to handle the person identification based on hand veins in real time. With a minimal distance measure of 2 pixels for False Feature Elimination, it has a True Acceptance Rate of 65% and a False Rejection Rate of 5%. The performance rises drastically with increasing pixel distance and will therefore be camera sensitive.
Original languageEnglish
Title of host publicationProceedings SSoCC
Publication statusPublished - 2006
EventSSoCC (Swedish System-on-Chip Conference), 2006 - Kolmården, Kålmården, Sweden
Duration: 2006 May 42006 May 5

Conference

ConferenceSSoCC (Swedish System-on-Chip Conference), 2006
Country/TerritorySweden
CityKålmården
Period2006/05/042006/05/05

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering

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