Hand Veins Feature Extraction using DT-CNNs

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

Abstract

As the identification process is based on the unique patterns of the users, biometrics technologies are expected to provide highly secure authentication systems. The existing systems using fingerprints or retina patterns are, however, very vulnerable. One’s fingerprints are accessible as soon as the person touches a surface, while a high resolution camera easily captures the retina pattern. Thus, both patterns can easily be “stolen” and forged. Beside, technical considerations decrease the usability for these methods. Due to the direct contact with the finger, the sensor gets dirty, which decreases the authentication success ratio. Aligning the eye with a camera to capture the retina pattern gives uncomfortable feeling. On the other hand, vein patterns of either a palm of the hand or a single finger offer stable, unique and repeatable biometrics features.
A fingerprint-based identification system using Cellular Neural Networks has already been proposed by Gao. His system covers all stages of a typical fingerprint verification procedure from Image Preprocessing to Feature Matching. This paper performs a critical review of the individual algorithmic steps. Notably, the operation of False Feature Elimination is applied only once instead of 3 times. Furthermore, the number of iterations is limited to 1 for all used templates. Hence, the computational need of the feedback contribution is removed. Consequently the computational effort is drastically reduced without a notable chance in quality. This allows a full integration of the detection mechanism. The system is prototyped on a Xilinx Virtex II Pro P30 FPGA.

Details

Authors
  • Suleyman Malki
  • Lambert Spaanenburg
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering

Keywords

  • Hand-Vein Recognition, Image Processing, Field-Programmable Gate-Array, Network on a Chip, Cellular Neural Network
Original languageEnglish
Title of host publicationProceedings of SPIE, the International Society for Optical Engineering
PublisherSPIE
Volume6590
Publication statusPublished - 2007
Publication categoryResearch
Peer-reviewedYes
EventInternational Symposium on Microtechnologies for the New Millennium, 2007 - Maspalomas, Maspalomas, Gran Canaria, Spain
Duration: 2007 May 22007 May 4

Publication series

Name
Volume6590

Conference

ConferenceInternational Symposium on Microtechnologies for the New Millennium, 2007
CountrySpain
CityMaspalomas, Gran Canaria
Period2007/05/022007/05/04