Texture Analysis in Thermal Infrared Imaging for Classification of Raynaud’s Phenomenon

The aim of this study is to discuss a supervised classification approach for the differential diagnosis of Raynaud’s Phenomenon on the basis of functional infrared imaging data. The classification of data from healthy subjects and from patients suffering for primary and secondary Raynaud’s Phenomenon is based on a large number of features extracted from the images. The performance of different classifiers, together with the problem of variable extraction and selection will be discussed for a data set collected at ITAB laboratory.