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 recieved 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 them 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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© 1997 Springer-Verlag Berlin Heidelberg
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Cha, nH. (1997). Fast image template and dictionary matching algorithms. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63930-6_143
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DOI: https://doi.org/10.1007/3-540-63930-6_143
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