Template matching
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Template matching is a technique in Digital image processing for finding small parts of an image which match a template image. It can be used in manufacturing as a part of quality control,[1] a way to navigate a mobile robot,[2] or as a way to detect edges in images.[3]
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[edit] Approach
There are different approaches to accomplishing template matching. Some are more performant than others, and some find better matches.
The simpliest way to perform template matching is to loop through all the pixels in the search image and compare them to the pattern. While this method is simple to implement and understand, it is one of the slowest methods.
A faster method is to reduce the image into smaller images, and then search the smaller images. After finding matches in the smaller images, that information is used in the larger image as a center location. The larger image is then searched in a small window to find the best location of the pattern. Other methods can handle problems such as translation, scale and image rotation.[4]
[edit] References
- ^ Aksoy, M. S., O. Torkul, and I. H. Cedimoglu. "An industrial visual inspection system that uses inductive learning." Journal of Intelligent Manufacturing 15.4 (August 2004): 569(6). Expanded Academic ASAP. Thomson Gale.
- ^ Kyriacou, Theocharis, Guido Bugmann, and Stanislao Lauria. "Vision-based urban navigation procedures for verbally instructed robots." Robotics and Autonomous Systems 51.1 (April 30, 2005): 69-80. Expanded Academic ASAP. Thomson Gale.
- ^ WANG, CHING YANG, Ph.D. "EDGE DETECTION USING TEMPLATE MATCHING (IMAGE PROCESSING, THRESHOLD LOGIC, ANALYSIS, FILTERS)". Duke University, 1985, 288 pages; AAT 8523046
- ^ Yuan, Po, M.S.E.E. "Translation, scale, rotation and threshold invariant pattern recognition system". The University of Texas at Dallas, 1993, 62 pages; AAT EP13780
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[edit] External links
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