Advertisement

Intelligent Information System for Interpretation of Dermatoglyphic Patterns of Down’s Syndrome in Infants

  • Hubert Wojtowicz
  • Wieslaw Wajs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7197)

Abstract

The paper describes design of an intelligent information system for assessment of dermatoglyphic indices of Down’s syndrome in infants. The system supports medical diagnosis by automatic processing of dermatoglyphic prints and detecting features indicating presence of genetic disorders. Application of image processing and pattern recognition algorithms in pattern classification of fingerprints and prints of hallucal area of the sole is described. Application of an algorithm based on multi-scale pyramid decomposition of an image is proposed for ridge orientation calculation. A method of singular points detection and calculation of ATD angle of the palm print is presented. Currently achieved results in dermatoglyphic prints enhancement, classification and analysis are discussed. Scheme used in classification of dermatoglyphic prints is described. RBF and triangular kernel types are used in the training of SVM multi-class systems generated with one-vs-one scheme. Results of experiments conducted on the database of Collegium Medicum of the Jagiellonian University in Cracow are presented.

Keywords

Fingerprint Image Palmprint Image Intelligent Information System Radial Loop Telemedical System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chikkerur, S., Cartwright, A.N., Govindaraju, V.: Fingerprint image enhancement using STFT analysis. Pattern Recognition 40, 198–211 (2007)CrossRefzbMATHGoogle Scholar
  2. 2.
    Cummins, H., Midlo, C.: Fingerprints, palms and soles - Introduction to Dermatoglyphics. Dover Publications Inc., New York (1961)Google Scholar
  3. 3.
    Feng, X.G., Milanfar, P.: Multiscale principal components analysis for image local orientation estimation. In: Proc. of the 36th Asilomar Conf. on Signals, Systems and Computers, vol. 1, pp. 478–482 (2002)Google Scholar
  4. 4.
    Fleuret, F., Sahbi, H.: Scale-invariance of support vector machines based on the triangular kernel. In: Proc. of the IEEE Int. Conf. on Computer Vision, ICCV (2003)Google Scholar
  5. 5.
    Preuss, M.: A screening test for patients suspected of having Turner syndrome. Clinical Genetics (10), 145–155 (1976)Google Scholar
  6. 6.
    Reed, T.: Dermatoglyphics in Down’s syndrome. Clinical Genetics (6), 236 (1974)Google Scholar
  7. 7.
    Reed, T.E., et al.: Dermatoglyphic nomogram for the diagnosis of Down’s syndrome. J. Pediat. (77), 1024–1032 (1970)Google Scholar
  8. 8.
    Tornjova-Randelova, S.G.: Dermatoglyphic characteristics of patients with Turners syndrome. Medicine Anthropologie 43(4), 96–100 (1990)Google Scholar
  9. 9.
    Yin, Y., Weng, D.: A New Robust Method of Singular Point Detection from Fingerprint. In: Proc. of Int. Symposium on Information Science and Engieering. IEEE (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hubert Wojtowicz
    • 1
  • Wieslaw Wajs
    • 2
  1. 1.Faculty of Mathematics and Nature, Institute of Computer ScienceUniversity of RzeszowRzeszowPoland
  2. 2.Faculty of Electrical Engineering, Institute of AutomaticsAGH University of Science and TechnologyCracowPoland

Personalised recommendations