А.L. Tyukin - Post-graduate Student, P.G. Demidov Yaroslavl State University. E-mail: tyukin.alexx@gmail.co I.М. Lebedev - Post-graduate Student, P.G. Demidov Yaroslavl State University. E-mail: ilyaleb@gmail.com А.L. Priorov - Dr.Sc. (Eng.), Associate Professor, P.G. Demidov Yaroslavl State University. E-mail: andcat@yandex.ru

In present work digital image processing algorithm for indoor positioning tasks is considered. Beacons with color code are taken like reference points. They represent a passive device with three fields of different color. Input data for algorithm is a video stream from usual video camera. Algorithm represents consistent processing of the frame from video stream. Algorithm includes next steps: filtering image, conversion from RGB model to HSV model and detection a color combination of the beacons on the image. Then algorithm constructs relational map, which represents beacons location relative video camera optic axis. The relational map is constructed based on relatively size of the beacons on the image. Coordinates location of all beacons indoor are known. Based on these results the mobile platform coordinates are calculated and its location is indicated in the absolute map. The absolute map is an image of a room or space plan where the mobile platform moves. The calculation of beacons coordinates in the space achieved due to two different methods usage: the three-dimensional affine transformations and gradient descent. Algorithm was investigated in different environment conditions and estimate of work quality was conducted. Algorithm was investigated for different type of lighting, for different illumination level and for the influence of «camera-beacon» distance was investigated. The estimate of work quality was being conducted based on detection accuracy location of the mobile platform. Accuracy parameter is a deviation of the results obtained from the true values of mobile platform location. The investigations show the efficiency of the algorithm and the work quality estimate demonstrates applicability of the algorithm for indoor positioning tasks.

 

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