Two step template matching method with correlation coefficient and genetic algorithm

Authors:
Gyeongdong Baek;Sungshin Kim
Affiliations:
School of Electrical Engineering, Pusan National University, Busan, Korea;School of Electrical Engineering, Pusan National University, Busan, Korea
Venue:
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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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.