Electronic digital image stabilization technique plays important roles in video surveillance or object acquisition.
Researchers have presented many useful algorithms, which can be classified to three kinds: gray based methods,
transformation based methods and feature based methods. When scenario is simple or flat, feature based methods
sometimes have imperfect results. Transformation based methods usually accompany large computation cost and high
computation complexity. Here we presented an algorithm based on gray projection which divided the whole image into
four sub-regions: the upper one, the bottom one, the left one and the right one. For making the translation estimation
easier, a central region is also chosen. Then the gray projections of the five sub-regions were counted. From the five pairs
of gray projections five group offsets including rotation and translation were obtained via cross correlation between
current frame and reference frame gray projections. Then according to the above offsets, the required parameters can be
estimated. The expected translation parameters(x axis offset and y axis offset) can be estimated via the offsets from the
central region image pair, the rotation angle can be calculated from the left four groups offsets. Finally, Kalman filter was
adopted to compute the compensation. Test results show that the algorithm has good estimation performance with less
than one pixel translation error and 10 percent rotation error. Based on this kind of gray projection algorithm, a real-time
electronic digital image stabilization system has been designed and implemented. System tests demonstrate the system
performance reaches the expected aim.