Palmprint identification using PalmCodes

Ajay Kumar Pathak, Helen C. Shen

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

62 Citations (Scopus)


This paper investigates a new approach for the palmprint identification using Real Gabor Function (RGF) filtering. Inkless composite hand images have been used to automatically extract the palmprints from peg-free imaging setup. These palmprints, after normalization, are subjected to selective feature sampling by a bank of RGF. Each of these filtered images has been used to extract significant features (PalmCode) from each of 6 concentric circular bands. Our preliminary experimental results using 400 low-resolution palmprint images achieve the recognition rate of 97.50% and also illustrate the shortcomings of results presented in earlier work. The results show the uniqueness of palmprint texture, even in the two hands of an individual and its possible use in biometrics based personal recognition.
Original languageEnglish
Title of host publicationProceedings - Third International Conference on Image and Graphics
Number of pages4
Publication statusPublished - 1 Dec 2004
EventProceedings - Third International Conference on Image and Graphics - Hong Kong, Hong Kong
Duration: 18 Dec 200420 Dec 2004


ConferenceProceedings - Third International Conference on Image and Graphics
Country/TerritoryHong Kong
CityHong Kong

ASJC Scopus subject areas

  • Engineering(all)

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