Vein feature extraction using DT-CNNs

Suleyman Malki, Y Fuqiang, Lambert Spaanenburg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

21 Citations (SciVal)


Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Security systems based on fingerprints and retina patterns have been widely developed, but can be easily falsified. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper an existing feature extraction algorithm, that has been developed for fingerprint recognition, is adapted for vein recognition. The algorithm has been implemented as cellular neural network and realized on a field-programmable gate-array. The detection quality is comparable to the 99.45% reached earlier by direct image comparison, but suffers from the image resolution sensitivity of the false feature elimination
Original languageEnglish
Title of host publication10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA '06.
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)1-4244-0640-4
Publication statusPublished - 2006
Event10th International Workshop on Cellular Neural Networks and their Applications (CNNA) - Istanbul
Duration: 2006 Aug 282006 Aug 30


Conference10th International Workshop on Cellular Neural Networks and their Applications (CNNA)

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering


  • Field Programmable Gate Arrays
  • Discrete-Time Cellular Neural Networks
  • Vein Feature Extraction.


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