Fast template matching algorithm based on boundary cross correlation and image integration
Zhong Shi-ming · Journal of Computer Applications · 2009
A fast template matching algorithm was presented based on the theory of normalize cross correlation(NCC).With the goal of accelerating the matching speed and yielding exactly the same result as other matching methods,it is applied to calculate the similarity of bounded cross correlation and image integration.In this process,NCC must calculate cross correlation and self-correlation at each point.Self-correlation was calculated only first and then Holder inequality was applied.With the given threshold,it can remove the unsatisfied point,and reduce the complex computation of cross correlation,significantly accelerate template matching.The advantage of image integration is in the process of matching the integration of sub-image can be obtained quickly by the integration of the whole image calculated before matching.The proposed algorithm has been applied in the wire-bonder image recognition system,and the experiment results show that template matching algorithm is of fast speed and high accuracy and this algorithm has practical value.