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Efficient Algorithms for Image Template and Dictionary Matching

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Abstract

Given a large text image and a small template image, the Template Matching Problem is that of finding every location within the text which looks like the pattern. This problem, which has received attention for low-level image processing, has been formalized by defining a distance metric between arrays of pixels and finding all subarrays of the large image which are within some threshold distance of the template. These so-called metric methods tends to be too slow for many applications, since evaluating the distance function can take too much time. We present a method for quickly eliminating most positions of the text from consideration as possible matches. The remaining candidate positions are then evaluated one by one against the template for a match. We are still guaranteed to find all matching positions, and our method gives significant speed-ups. Finally, we consider the problem of matching a dictionary of templates against a text. We present methods which are much faster than matching the templates individually against the input image.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, State University of New York, Buffalo

    Sung-Hyuk Cha

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  1. Sung-Hyuk Cha
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Cha, SH. Efficient Algorithms for Image Template and Dictionary Matching. Journal of Mathematical Imaging and Vision 12, 81–90 (2000). https://doi.org/10.1023/A:1008309026555

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