Grayscale Template-Matching Invariant to Rotation, Scale, Translation, Brightness and Contrast

  • Hae Yong Kim
  • Sidnei Alves de Araújo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)

Abstract

In this paper, we consider the grayscale template-matching problem, invariant to rotation, scale, translation, brightness and contrast, without previous operations that discard grayscale information, like detection of edges, detection of interest points or segmentation/binarization of the images. The obvious “brute force” solution performs a series of conventional template matchings between the image to analyze and the template query shape rotated by every angle, translated to every position and scaled by every factor (within some specified range of scale factors). Clearly, this takes too long and thus is not practical. We propose a technique that substantially accelerates this searching, while obtaining the same result as the original brute force algorithm. In some experiments, our algorithm was 400 times faster than the brute force algorithm. Our algorithm consists of three cascaded filters. These filters successively exclude pixels that have no chance of matching the template from further processing.

Keywords

Template matching RST-invariance segmentation-free shape recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hae Yong Kim
    • 1
  • Sidnei Alves de Araújo
    • 1
  1. 1.Escola Politécnica, Universidade de São PauloBrazil

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