Fast Normalized Cross Correlation Based on Adaptive Multilevel Winner Update View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2007-01-01

AUTHORS

Shou-Der Wei , Shang-Hong Lai

ABSTRACT

In this paper we propose a fast normalized cross correlation (NCC) algorithm for pattern matching based on combining adaptive multilevel partition with the winner update scheme. This winner update scheme is applied in conjunction with an upper bound for the cross correlation derived from Cauchy-Schwarz inequality. To apply the winner update scheme, we partition the summation of cross correlation into different levels with the partition order determined by the gradient energies of the partitioned regions in the template. Thus, this winner update scheme can be employed to skip the unnecessary calculation. Experimental results show the proposed algorithm is very efficient for image matching under different lighting conditions. More... »

PAGES

413-416

Book

TITLE

Advances in Multimedia Information Processing – PCM 2007

ISBN

978-3-540-77254-5
978-3-540-77255-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-77255-2_48

DOI

http://dx.doi.org/10.1007/978-3-540-77255-2_48

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038338356


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