New method for subject identification based on palm print

Heber I. Mejía-Cabrera, Rafael Antón Chiclayo, J. Nicolás Flores, Victor Tuesta-Monteza, Manuel G. Forero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Nowadays, new security and protection systems for citizens are being developed, since criminals have found techniques to violate those already known, such as those based on fingerprints, facial recognition, iris and voice. Thus, using biometric data, new systems are being developed that are more secure, infallible and fast to identify each person, making it impossible to impersonate them, as has happened with other methods. Recently new identification methods have been proposed based on hand geometry and palmprint based on texture techniques for the identification of hand characteristics such as ridges, edges, points, and textures. Following this trend, this paper presents a method based on the detection of the palm print, acquired by contact, through the use of a scanner. For this purpose, the image is segmented to detect the silhouette of the hand and delimit the working area, achieving greater speed in identification. The images are then used as input to a convolutional neural network VGG 16 for learning and identification of subjects, achieving 100% accuracy.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XLIII
EditorsAndrew G. Tescher, Touradj Ebrahimi
ISBN (Electronic)9781510638266
StatePublished - 2020
Externally publishedYes
EventApplications of Digital Image Processing XLIII 2020 - Virtual, Online, United States
Duration: 24 Aug 20204 Sep 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceApplications of Digital Image Processing XLIII 2020
Country/TerritoryUnited States
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2020 SPIE


  • Biometry
  • Convolutional neural networks
  • Fingerprints
  • Impersonation
  • Iris prints
  • Palmprint
  • Protection methods
  • Security methods


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