Computation of the normalized cross-correlation by fast Fourier transform

Artan Kaso

PLOS ONE, 2018, vol. 13, issue 9, 1-16

Abstract: The normalized cross-correlation (NCC), usually its 2D version, is routinely encountered in template matching algorithms, such as in facial recognition, motion-tracking, registration in medical imaging, etc. Its rapid computation becomes critical in time sensitive applications. Here I develop a scheme for the computation of NCC by fast Fourier transform that can favorably compare for speed efficiency with other existing techniques and may outperform some of them given an appropriate search scenario.

Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0203434 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 03434&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0203434

DOI: 10.1371/journal.pone.0203434

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().