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Proceedings Paper

Planar curve smoothing for pattern recognition
Author(s): Kidiyo Kpalma; Joseph Ronsin
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Paper Abstract

In this paper, we present a method in the context of pattern characterization. This method is based on the analysis of closed contours of planar objects. The input contour is, first, separated into its x and y coordinates to generate two 1D signals. Both signals are then progressively low-pass filtered with a Gaussian kernel by decreasing the filter bandwidth. The output signals X and Y are then scaled so that the reconstructed contour and the original one can intersect. By doing so, we generate the so called IPM (Intersection Points Map) function that yields interesting attributes for pattern characterisation. The experimental results obtained by applying this method to various contours show that the IPM function is strongly related to the input contour and is rotation and translation invariant. It is also invariant under scale chance for a large range of scales. According to the experimental results, this function appears to be computationally very simple and to provide well-adapted features in the context of pattern recognition.

Paper Details

Date Published: 25 September 2003
PDF: 4 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538863
Show Author Affiliations
Kidiyo Kpalma, Institut National des Sciences Appliquees de Rennes (France)
Joseph Ronsin, Institut National des Sciences Appliquees de Rennes (France)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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