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Application of stochastic geometry methods to pattern recognition is analysed. The paper is based on Tracetransformations of original images into images on the Möbius band. Based on the new geometric transformation, a new approach towards the construction of features, independent of images’ motions or their linear transformations, is put forward. A prominent characteristics of the group of features under consideration is that we can represent each of them as a consecutive composition of three functionals. The paper considers the application of three-functional structure of recognition feature to image pre-processing. Feature can be invariant or sensitive to the group of all motions transformation and linear deformation of objects depending of functionals selection. Thus sensitive features are suitable to determine the parameters of translation. It is an important task for robotics.

PATTERN RECOGNITION FEATURE AND IMAGE PROCESSING THEORY ON THE BASIS OF STOCHASTIC GEOMETRY