P.V. Smirnov - Post-graduate Student, Ulyanovsk State Technical University A.G. Tashlinskii - Dr. Sc. (Eng.), Professor, Head of Department «Radio Engineering», Ulyanovsk State Technical University

The paper carries out a comparative analysis of various approaches to identify area of moving object in image sequence using pixel-by-pixel estimation of inter-frame shifts of all nodes of the reference image. It studies projections and polar parameters of shift vectors of reference image points corresponding to the nodes as their estimated parameters. The paper proposes the method for estimating shift vectors - field. The method finds two sets of shift estimates of all nodes of the reference image using stochastic gradient descent algorithm and then processes them jointly. The joint processing allows compensating inertia of the recursive estimation. The paper studies two methods to find a set of shift estimates. The first method uses stochastic gradient descent algorithm to sequentially process all nodes of the image row-by-row. It processes each row bidirectionally (from the left to the right and from the right to the left). However this method does not consider correlation between adjacent rows and processes images as one-dimensional signals. Therefore the second method uses the correlation between adjacent rows to increase the efficiency of moving object area identification. The method processes rows one after the other with change in direction after each row and performs the joint processing of the adjacent rows - estimates obtained in opposite directions. This method shows significantly better results. The joint processing of sets of shift estimates uses correlation coefficient maximum as a criterion of shift vectors - field formation. It provides not only low mean value and variance of estimation error both in motion area and outside it but the oscillations are also low.

 

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