A New Approach for Hand-Palm Recognition

  • Khalid Saeed
  • Marcin Werdoni


A new algorithm for human recognition by hand-palm images is presented in this paper. The suggested approach is based on characteristics of the minimal eigenvalues obtained from Toeplitz matrices for image description. The recognition steps in the algorithm use both classical and new approaches. The achieved results are promising although of not very high rate of classification. The effectiveness of the recognition has achieved 100% in small classes and about 70% in large classes using the new trend of minimal eigenvalues. It reaches, however, a 100% rate of classification following the classical methods of comparison and classification for even bigger classes.

Key words

Hand-Geometry Human Identification Classification Toeplitz Biometrics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Saeed K., Werdoni M., “An Experimental Algorithm for Human Identification by Hand-Palm Geometry,” 10th International Conference on Advanced Computer Systems-ACS’03, October 22–24, Miedzyzdroje 2003.Google Scholar
  2. [2]
    Gonzales R. C, Woods R.E., “Digital Image Processing”, Prentice-Hall, New Jersey 2002.Google Scholar
  3. [3]
    Werdoni M., “An Experimental Algorithm for Person Identification by Recognizing Geometrical Parameters of His Hand”, M.Sc. Thesis, Bialystok University of Technology, 2003.Google Scholar
  4. [4]
    Saeed K., “Computer Graphics Analysis: A Criterion for Image Feature Extraction and Recognition,” MGV-International Journal on Machine Graphics and Vision, Institute of Computer Science, Polish Academy of Sciences, Volume 10, Issue 2, Warsaw 2001, pp. 185–194.Google Scholar
  5. [5]
    Saeed K., “Object Classification and Recognition Using Toeplitz Matrices,” Artificial Intelligence and Security in Computing Systems, edited by Jerzy Soldek and Leszek Drobiazgiewicz, The Kluwer International Series in Engineering and Computer Science, Volume 752, September 2003.Google Scholar
  6. [6]
    Saeed K., Tabędzki M., Adamski M., “A New Approach for Object-Feature Extract and Recognition,” The 9th International Conference ACS (Advanced Computer Systems), pp. 389–397, 23–25 October, Międzyzdroje 2002.Google Scholar
  7. [7]
    Kuchariew G. A., “Biometric Systems — Methods and Approaches of Human Personality Identification,” Politechnic Press (in Russian), Petersburg 2001.Google Scholar
  8. [8]
    Sanchez-Reillo R., Sanchez-Avila C, Gonzalez-Marcos A.: “Biometric Identification through Hand Geometry Measurements,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, October 2000, pp. 1168–1171.CrossRefGoogle Scholar
  9. [9]
    Lindeburg L., “Scale-Space Theory in Computer Vision” Kluwer Academic Publishers, Boston 1994.Google Scholar
  10. [10]
    Rao A. R., Jain R. C, “Computerized Flow Field Analysis: Oriented Texture-Fields” IEEE Trans. Pattern Analysis, and Machine Intelligence, vol. 14, no. 7, pp. 693–709, July 1992.CrossRefGoogle Scholar
  11. [11]
    Saeed K., Kozlowski M., “An Image-Based System for Spoken-Letter Recognition,” Lecture Notes in Computer Science, Springer-Verlag, pp. 494–502, 10th CAIP Int. Conference on Computer Analysis of Images and Patterns, August 25–27, Groningen, The Netherlands 2003.Google Scholar
  12. [12]
    Saeed K., “Efficient Method for On-Line Signature Verification” Proc. ICCVG Int. Conf. on Computer Vision and Graphics, Zakopane, Poland, pp. 635–640.Google Scholar
  13. [13]
    Saeed K., “A New Approach in Image Classification” Proc. 5th International Conference on Digital Signal Processing and its Applications-DSPA’03, Vol. 1, pp. 49–52, Moscow 2003.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Khalid Saeed
    • 1
  • Marcin Werdoni
    • 1
  1. 1.Faculty of Computer ScienceBialystok University of TechnologyBialystokPoland

Personalised recommendations