A biometric identification system


The multiplatform system for automatic person identification, based on the fusion of palm, fingers and hand geometry features.

Key features

  • a fusion of palm and hand geometry features
  • a single sensor is used for extracting palm and hand geometry features (fusion at the feature extraction level).
  • no pegs, the user has to put his hand on the input device with fingers spread naturally.
  • translation and rotation of the hand is allowed.
  • spatial resolution of the images is 180 dpi / 256 grey levels.
  • a fusion at the confidence level (accept/reject decision).
  • at the fusion level the neural network is used
  • system was written in C++ and tested on Linux and WIN32 platforms. GUI for demo program was written using FOX toolkit.

Experimental results

  • The biometric identification system was tested using a database of 112 persons who were not used in the training phase.
  • At least five images of each person's hand were captured, thus more than 560 images were made available. In the enrolment phase we used three images, and so for testing the users there were at least two available images. For the impostors at least five images were available for testing.
  • There was more then 900000 matching between samples during the experiment.
  • False Reject Rate (FRR) and False Accept Rate (FAR):
        Learn database
    (54 persons)
    Test database
    (112 persons)
    FRR [%] 0.00 0.38
    FAR [%] 0.00 0.00
    FRR [%] 0.00 0.57
    FAR [%] 0.00 0.00
    FRR [%] 0.79 1.90
    FAR [%] 0.00 0.00
  • Execution time:
    Linux130 ms60 ms< 1 ms
    MS Windows 2000200 ms< 1 ms< 1 ms
    Tested on Pentium III 1000Mhz, using database of 112 persons, each person was represented with 7 samples.

Hand samples

Hand samples with extracted finger features and palm area.
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Extracted palm area features.



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