Abstract: Image stabilization is the key for accurate docking operations of robots with
vision. The whole algorithm of image stabilization is established, including images kinematics
model, KLT feature pixels detecting, SAD feature pixels matching and filters. Kalman and FIR
filters are designed for smoothing images motion parameters and built in MATLAB. Simulation of
filter of motion un-intended parameters is implemented to indicate removing jitter effect. Kalman
filter is compared with FIR filter. Comparison curves and tables are given , which demonstrate
that Kalman filter is better than FIR in robot vision image stabilization process. Based on VC++
and OpenCV, image stabilization software is programmed, and experiments are completed on
double moving robots docking operation platform. The algorithm running time is less than the
sampling period, and the precision and real-time demands are contented.

Key words: machine vision, image stabilization, robot docking, filter modeling, jitter
removing