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In this article, the research results of the usage of selected methods of the analysis of images for the recognition of hand gestures in human-computer interaction was depicted. The usage of this type of interaction is important in case of the so-called wearable computers (computer is integrated with the work clothing of an operator. For the recognition of gestures, the combination of two methods associated with the image processing was suggested and that is the Chan-Vese active contour model enabling to recognize objects on a given image, based on the curve evolution technique, Mumford-Shah functional, level-sets and the methods to create shapes with the use of Fourier descriptors. For the classification criteria as a compatibility measure a scalable Mahalanobis distance was used.

The Structure of Classifiers of Hand Gestures with the Use of the Active Contour Model and Fourier Descriptors