Fingerprint classification using computational intelligence algorithms in medical diagnostics

Fingerprint classification is used by anthropologist in detection of genetic disorders in infants.This paper describes application of image processing and pattern recognition methods in classification of fingerprints. Fingerprint classifiers, which are part of an automatic system for rapid screen diagnosing of trisomy 21 (Down Syndrome) in infants, are created and discussed. The system is a tool supporting medical decision by automatic processing of dermatoglyphic prints and detecting features indicating presence of genetic disorder. Images of dermatoglyphic prints are pre-processed before the classification stage to extract features analyzed by the Support Vector Machines algorithm. Application of an algorithm based on multi-scale pyramid decomposition of the image is proposed for the ridge orientation calculation. RBF and triangular kernel types are used in the training of SVM multi-class systems generated with the one–vs–one scheme. The experiments conducted on the database of the Collegium Medicum Jagiellonian University in Cracow show the effectiveness of the proposed approach in classification of infants’ fingerprints.