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Computation of the normalized cross-correlation by fast Fourier transform

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  • Artan Kaso

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.

Suggested Citation

  • Artan Kaso, 2018. "Computation of the normalized cross-correlation by fast Fourier transform," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0203434
    DOI: 10.1371/journal.pone.0203434
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    Cited by:

    1. Shien Ri & Jiaxing Ye & Nobuyuki Toyama & Norihiko Ogura, 2024. "Drone-based displacement measurement of infrastructures utilizing phase information," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    2. Faisal Alqahtani & Ema Michael Abraham & Essam Aboud & Murad Rajab, 2022. "Two-Dimensional Gravity Inversion of Basement Relief for Geothermal Energy Potentials at the Harrat Rahat Volcanic Field, Saudi Arabia, Using Particle Swarm Optimization," Energies, MDPI, vol. 15(8), pages 1-30, April.

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