Very Fast Template Matching

  • H. Schweitzer
  • J. W. Bell
  • F. Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2353)


Template matching by normalized correlations is a common technique for determine the existence and compute the location of a shape within an image. In many cases the run time of computer vision applications is dominated by repeated computation of template matching, applied to locate multiple templates in varying scale and orientation. A straightforward implementation of template matching for an image size n and a template size k requires order of kn operations. There are fast algorithms that require order of n log n operations. We describe a new approximation scheme that requires order n operations. It is based on the idea of “Integral-Images”, recently introduced by Viola and Jones.


Normalize Correlation Polynomial Approximation Template Match Centralize Moment Integral Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • H. Schweitzer
    • 1
    • 2
  • J. W. Bell
    • 1
    • 2
  • F. Wu
    • 1
    • 2
  1. 1.The University of Texas at DallasRichardsonUSA
  2. 2.Voxar AGPlanoUSA

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