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Optimization of information signs recognition methods for the problem of indoor navigation
Lebedev Leonid Ivanovich

PhD in Physics and Mathematics

Leading Researcher, Lobachevsky National Research Nizhny Novgorod State University

603950, Russia, Nizhegorodskaya oblast', g. Nizhnii Novgorod, pr. Gagarina, 23

Osipov Mikhail Pavlovich

PhD in Technical Science

Leading Researcher, Lobachevsky National Research Nizhny Novgorod State University

603950, Russia, Nizhegorodskaya oblast', g. Nizhnii Novgorod, pr. Gagarina, 23



The paper proposes the solution of a number of problems related to the optimization of recognition of information signs by the correlation-extremal contour method based on the evaluation of similarity invariant with respect to affine transformations.A description is given of a speed-efficient algorithm for obtaining regions of a certain color and its parallelization. It is shown that solving this problem allows reducing both the number of objects presented for recognition and the number of standards used, as well as obtaining a better contour description of objects and, therefore, significantly increasing the speed of the recognition algorithm itself. The solution of the problem of optimization of calculations in the recognition algorithm itself is given. It is shown that one of the ways to solve this problem for a particular chosen recognition algorithm is to parallelize the computation of the similarity estimate by the affine transformation parameters. Another presented way of solving the problem of optimization of computations was focused on obtaining estimates of the similarity of the current standard with objects from the local area of the image, which is determined on the basis of the parameters of affine transformation and dimensions of the standard. It is noted that the created algorithmic software allows to solve problems of recognition of information objects in real time.

Keywords: affine transformation, optimization, color segmentation, parallel algorithm, pattern recognition, image processing, computer graphics, standart image, adaptive description, correlation-extreme contour method



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