Abstract
In this paper we describe the Euclidean signature curves for two dimensional closed curves in the plane and will give a discrete numerical method for finding such invariant curves. Further we describe an analog of Latent Semantic Analysis (LSA) and present data and noise reduction techniques as well as an optimal combination of normalizing transformations to categorize signature curves. We will then introduce a system for determining the correct category for a new object from a pre-existing database of information on objects and give an example for sorting out leaves of two types of trees regardless of their orientation using their signature curves.
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Shakiban, C., Lloyd, R. (2005). Classification of Signature Curves Using Latent Semantic Analysis. In: Li, H., Olver, P.J., Sommer, G. (eds) Computer Algebra and Geometric Algebra with Applications. IWMM GIAE 2004 2004. Lecture Notes in Computer Science, vol 3519. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499251_13
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DOI: https://doi.org/10.1007/11499251_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26296-1
Online ISBN: 978-3-540-32119-4
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