Circular projection for pattern recognition

Authors:
Guangyi Chen;Tien Dai Bui;Sridhar Krishnan;Shuling Dai
Affiliations:
Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada,Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Can ...;Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada;Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada;State Key Lab. of Virtual Reality Technology and Systems, Beihang University, Beijing, P.R. China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

Citing 3
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Abstract

There are a number of methods that transform 2-D shapes into periodic 1-D signals so that faster recognition can be achieved. However, none of these methods are both noise-robust and scale invariant. In this paper, we propose a circular projection method for transforming 2-D shapes into periodic 1-D signals. We then apply a number of feature extraction methods to the 1-D signals. Our method is invariant to the translation, rotation and scaling of the 2-D shapes. Also, our method is robust to Gaussian white noise. In addition, it performs very well in terms of classification rates for a well-known shape dataset.