Classification of Plantar Dermatoglyphic Patterns for the Diagnosis of Down’s Syndrome

Abstract

Classification of patterns of the hallucal area of sole is one of the tasks of dermatoglyphic analysis. The paper describes pattern recognition and image processing methods applied to the problem of the hallucal area of sole patterns classification. Contrast enhancement, segmentation and contextual filtration techniques are used to enhance quality of the images. Application of an algorithm based on multi-scale pyramid decomposition of an image is proposed for ridge orientation calculation. Hallucal area pattern classifiers, which are part of an automatic system for rapid screen diagnosing of trisomy 21 (Down’s 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 Support Vector Machines algorithm. RBF kernel type is used in the training of SVM multi-class systems generated with one-vs-one scheme. Experiments conducted on the database of Collegium Medicum of the Jagiellonian University in Cracow show effectiveness of the proposed approach in classification of infants’ dermatoglyphs.