A robust method for the recognition of palmprints

O Nibouche, Hui Wang, Sriram Varadarajan, Bryan Scotney

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Palmprint recognition has received in the last 20 years a great deal of the research community's attention. In this paper a new palmprint matching approach based on corner feature point extraction is proposed. A 72-element fixed-length descriptor is used to capture distinctive information of each feature point neighborhood and to build a measure of similarity whilst their coordinates provide a measure of proximity between the points. Matching two images takes into account both similarity and proximity measures which converts into a cost minimization problem. Our experiments carried out on a database of 250 prints from the Poly U database have yielded very good results evidenced by an EER of 0.31%.
Original languageEnglish
Title of host publication14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)978-1-5386-2940-6
Publication statusPublished - 23 Oct 2017

Bibliographical note

14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) ; Conference date: 29-08-2017 Through 01-09-2017


  • Feature extraction
  • Robustness
  • Databases
  • Coordinate measuring machines
  • Image resolution
  • Transforms
  • Eigenvalues and eigenfunctions


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