An Improved Fast Normalized Cross Correlation Algorithm

Abstract:

Some improvements were made for normalized cross correlation based on two criterions according to the characteristics of template and image and the interrelationship between them.The autocorrelation of the template was calculated at first,and the cross correlation between template and image was gained based on fast Fourier transform.Then the first criterion was used to shrink the range of the possible solutions, which could shorten the matching time;and the second criterion was applied to generating a more miniature set,in which the solution with the maximal normalized cross correlation was the global optimal solution.Experiments show that the normalized cross correlation based on the given criteria can speed the computing with an enhanced matching precision.