NDLI: Fast template matching with partial skipping using sub-template

Content Provider	IEEE Xplore Digital Library
Author	Qiao Zhang Huijie Gao Zhen Kang
Copyright Year	2012
Description	Author affiliation: State Key Lab. of Multi-spectral Information Processing Technology, Institute for Pattern Recognition and Artificial Intelligence, Huazhong Univ. of Sci. & Tech, Wuhan, 430074 (Qiao Zhang; Huijie Gao) \|\| School of Mathematic & Computer Science, Wuhan Polytechnic University, Wuhan, 430023 (Zhen Kang)
Abstract	This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the subtemplate size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.
Starting Page	889
Ending Page	892
File Size	673433
Page Count	4
File Format	PDF
ISBN	9781467301732
e-ISBN	9781467301749
DOI	10.1109/ICALIP.2012.6376739
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Correlation Signal processing algorithms Prediction algorithms Search problems Computational efficiency Pattern recognition
Content Type	Text
Resource Type	Article

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