Compensation of dynamic errors of video images with measuring information based on artificial neural networks - Подчашинський, Юрій Олександрович; Шаповалова, Оксана Олександрівна; Шавурський, Юрій Олександрович (Eastern-European Journal of Enterprise Technologies, 2014)
Algorithmic methods of compensating the dynamic video image errors with measuring information were considered. For example, it can be a video image of industrial products made of natural stone. These products need to be accurately controlled by the geometric parameters, which define the quality and aesthetic appearance of the product (linear dimensions and angles of the outer contour and geometric parameters of the structural elements of the finished surface). When forming the video images, dynamic errors appear which affect the accuracy of the geometric parameters of the products. These errors are caused by a non-ideal optical system of a video image forming device (the influence of a scattering point function) and the products movement in relation to the device during the manufacturing process (blurring of contours in the video). It was proposed to use an adaptive linear neural network for compensating the dynamic errors. The neural network implements a filter that restores a video image, improves the playback quality of the product contours and accuracy of their geometrical parameters. Weighting coefficients of the filter are adjusted by training the neural network in accordance with the current parameters of the video image dynamic distortion. This improves the accuracy of determining the geometric parameters in the production conditions of measurements.