An improved template matching method for object detection

Authors:
Nguyen Duc Thanh;Wanqing Li;Philip Ogunbona
Affiliations:
Advanced Multimedia Research Lab, ICT Research Institute, School of Computer Science and Software Engineering, University of Wollongong, Australia;Advanced Multimedia Research Lab, ICT Research Institute, School of Computer Science and Software Engineering, University of Wollongong, Australia;Advanced Multimedia Research Lab, ICT Research Institute, School of Computer Science and Software Engineering, University of Wollongong, Australia
Venue:
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Year:
2009

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Abstract

This paper presents an improved template matching method that combines both spatial and orientation information in a simple and effective way The spatial information is obtained through a generalized distance transform (GDT) that weights the distance transform more on the strong edge pixels and the orientation information is represented as an orientation map (OM) which is calculated from local gradient We applied the proposed method to detect humans, cars, and maple leaves from images The experimental results have shown that the proposed method outperforms the existing template matching methods and is robust against cluttered background.