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Modeling Shapes for Pattern Recognition: A Simple Low-Cost Spline-based ApproachVATAVU, R. D. , PENTIUC, S. G. , GRISONI, L. , CHAILLOU, C.
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spline, cubic polynomial, pattern recognition, algorithms, shape modeling, curves, approximation error, Haussdorff distance
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About this article
Date of Publication: 2008-04-02
Volume 8, Issue 1, Year 2008, On page(s): 67 - 71
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2008.01012
Web of Science Accession Number: 000259903500012
SCOPUS ID: 77955605589
We present a simple procedure for modeling shapes and trajectories of points using cubic polynomial splines. The procedure may prove useful for researchers working in the field of pattern recognition that are in the search of a simple functional representation for shapes and which are not particularly interested in diving into the hightheoretical aspects of more complex representations. The use of splines brings in a few advantages with regards to data dimensionality, speed and accuracy of processing, with minimal effort required for the implementation part. We describe several algorithms for data reduction, spline creation and query for which we provide pseudo code procedures in order to demonstrate the ease of implementation. We equally provide measurements on the approximation error and rate of data reduction.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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