NDLI: A multi-scale curve smoothing for generalised pattern recognition (MSGPR)

Content Provider	IEEE Xplore Digital Library
Author	Kpalma, K. Ronsin, J.
Copyright Year	2003
Description	Author affiliation: Groupe Image et Teledetection, Inst. Nat. des Sci. Appliquees, Rennes, France (Kpalma, K.; Ronsin, J.)
Abstract	In this paper, we introduce a new method for pattern characterisation in the context of pattern recognition. This method is based on the analysis of the contour of planar objects like the CSS (curvature scale space) method that uses the maxima of the curvature zero-crossing. The input contour is separated into two signals according to its coordinates x and y which are progressively low-pass filtered by decreasing the filter bandwidth. The output signals are then amplified so that the reconstructed contour and the input one have the same scale. By doing so, we detect the intersection points between both contours and then generate the intersection points map that defines features for pattern recognition. Since this method deals only with curve smoothing, it needs only a convolution operation. This way, one can reasonably hope that this method is faster than the CSS one with equivalent performances.
Starting Page	427
Ending Page	430
File Size	218590
Page Count	4
File Format	PDF
ISBN	0780379462
DOI	10.1109/ISSPA.2003.1224905
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-04
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Smoothing methods Pattern recognition Bandwidth Low pass filters Cascading style sheets Shape measurement Area measurement Character recognition Image recognition Image reconstruction
Content Type	Text
Resource Type	Article

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