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DOI: 10.14569/IJACSA.2015.061028
PDF

FRoTeMa: Fast and Robust Template Matching

Author 1: Abdullah M. Moussa
Author 2: M. I. Habib
Author 3: Rawya Y. Rizk

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 10, 2015.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Template matching is one of the most basic techniques in computer vision, where the algorithm should search for a template image T in an image to analyze I. This paper considers the rotation, scale, brightness and contrast invariant grayscale template matching problem. The proposed algorithm uses a sufficient condition for distinguishing between candidate matching positions and other positions that cannot provide a better degree of match with respect to the current best candidate. Such condition is used to significantly accelerate the search process by skipping unsuitable search locations without sacrificing exhaustive accuracy. Our proposed algorithm is compared with eight existing state-of-the-art techniques. Theoretical analysis and experiments on eight image datasets show that the proposed simple algorithm can maintain exhaustive accuracy while providing a significant speedup.

Keywords: template matching; pattern matching; brightness-contrast invariance; rotation invariance; scale invariance; sufficient condition

Abdullah M. Moussa, M. I. Habib and Rawya Y. Rizk, “FRoTeMa: Fast and Robust Template Matching” International Journal of Advanced Computer Science and Applications(IJACSA), 6(10), 2015. http://dx.doi.org/10.14569/IJACSA.2015.061028

@article{Moussa2015,
title = {FRoTeMa: Fast and Robust Template Matching},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.061028},
url = {http://dx.doi.org/10.14569/IJACSA.2015.061028},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {10},
author = {Abdullah M. Moussa and M. I. Habib and Rawya Y. Rizk}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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