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• DEVELOPMENT OF A METHOD FOR PERSONAL IDENTIFICATION BASED ON THE PATTERN OF PALM VEINS

  V.А. Chastikova, S.А. Zherlitsyn

  2022-11-01

  Abstract ▼

  The article describes the work on the creation of a neural network method for identifying
  a person based on the mechanism of scanning and analyzing the pattern of palm veins as a biometric
  parameter. As part of the study, the prerequisites, goals and reasons for which the deve lopment
  of a reliable biometric identification system is an important and relevant area of activity
  are described. A number of problems are formulated that are inherent in existing methods for
  solving the problem: the graph method and the method based on calculating the distance expressed
  in various interval metrics. The description of the principles of their work is given.
  The tasks solved by personal identification systems are formulated: comparison of the subject of
  identification with its identifier, which uniquely identifies this subject in the information system.
  A mechanism for reading a pattern of veins from the palm of the hand, developed for analyzing
  an image obtained with a digital camera sensitive to infrared radiation, is described. When the
  palm is in the frame, illuminated by the light of the near infrared range, the image obtained
  from the camera becomes noticeable pattern of veins, vessels and capillaries that lie under the
  skin. Depending on the organization, the identification system may, based on the provided identifier,
  determine the appropriate access subject or verify that the same identifier belongs to the
  intended subject. Three methods for further analysis of biometric data and personal identification
  are given: approaches based on categorical classification and binary classification, as well
  as a combined approach, in which identification is first used by the first method, and then, by
  the second, but already for a known access identifier defined on the first stage. The resulting
  architecture of the neural network for the categorical classification of the vein pattern is pr esented,
  a method for calculating the number of model parameters depending on the number of
  registered subjects is described. The main conclusions and experimental measurements of the
  accuracy of the system when implementing various methods are presented, as well as diagrams of
  changes in the accuracy of models during training. The main advantages and disadvantages of the
  above methods are revealed.