Abstract
This paper presents a rotation invariant template matching method based on two step matching process, cross correlation and genetic algorithm. In order to improve the matching performance, the traditional normalized correlation coefficient method is combined with genetic algorithm. Normalized correlation coefficient method computes probable local position of the template in the scene image. And genetic algorithm computes global position and rotation of the template in the scene image. The experimental results show that this algorithm has good rotate invariance, and high precision property.
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© 2009 Springer-Verlag Berlin Heidelberg
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Baek, G., Kim, S. (2009). Two Step Template Matching Method with Correlation Coefficient and Genetic Algorithm. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_10
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DOI: https://doi.org/10.1007/978-3-642-04020-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04019-1
Online ISBN: 978-3-642-04020-7
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