25 September 2003 Planar curve smoothing for pattern recognition
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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.538863
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kidiyo Kpalma, Kidiyo Kpalma, Joseph Ronsin, Joseph Ronsin, } "Planar curve smoothing for pattern recognition", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538863; https://doi.org/10.1117/12.538863
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