Calibration System for the Cross-Correlation Algorithm Based on OpenCV - Multimedia and Signal Processing - page 45

4 Conclusions

Cross-correlation algorithm first divides the image into a number of the sub-regions
with the same size, and then each pair sub-regions are calculated to obtain the velocity
vector, yielding statistical average velocity vectors. The choice of the sub-regions size
is particularly critical, made too small, and easy to produce more redundant data and
error; made too much, will lose details. Therefore, several tests are conducted to
select the sub-regions size. From which, it shows that the images with different densi-
ties, the size of the selected sub-area related with the movement of the particle dis-
placement. When the size of sub-region is four times larger than the displacement, the
speed information can be basically restored; the size of the sub-regions will not intro-
duce error. The above discussion laid a solid foundation for the applications of the
cross-correlation algorithm.

Acknowledgment. This work was supported by the general project of the Natural
Science Foundation of Fujian Province, and the general project of the Fujian Province
Department of Education Technology, and the research project of Fujian University
of Technology.

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