Open Access
Polynomial Approximation in Handwriting Recognition (Extended Abstract)
TLDR
Considering digital ink traces as plane curves provides a useful framework for handwriting recognition, and a single, coherent view leads to highly ecient methods with a high recognition rate.Abstract:
Considering digital ink traces as plane curves provides a useful framework for handwriting recognition. Characters may be represented as parametric curves approximated by certain truncated orthogonal series, mapping symbols to the lowdimensional vector space of series coecients. Many useful properties are obtained in this representation, allowing fast recognition based on small training sets. The beauty of this framework is that a single, coherent view leads to highly ecient methods with a high recognition rate. Furthermore, these truncated orthogonal series are subject to all the geometric techniques of symbolic-numeric polynomial algorithms.read more
References
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Journal ArticleDOI
Distance-based classification of handwritten symbols
Oleg Golubitsky,Stephen M. Watt +1 more
TL;DR: An implementation of the proposed classification scheme that will allow classification of a sample among hundreds of classes in a setting with strict time and storage limitations is discussed.
Proceedings ArticleDOI
Hybrid Mathematical Symbol Recognition Using Support Vector Machines
B. Keshari,Stephen M. Watt +1 more
TL;DR: Results from the experiments show that giving slightly higher weight to the on-line information produces better results, and the overall error rate of the hybrid system is lower than that of both the online and offline recognition systems when used in isolation.
Proceedings ArticleDOI
Representing and Characterizing Handwritten Mathematical Symbols through Succinct Functional Approximation
Bruce W. Char,Stephen M. Watt +1 more
TL;DR: Using a collection of mathematical writing samples, this work model on-line ink traces for a set of 219 symbols to "best fit" low-degree polynomial series and finds this style of characterization to be an attractive tool due to the suitability of the representation to computation and mathematical analysis.
Proceedings ArticleDOI
Online stroke modeling for handwriting recognition
Oleg Golubitsky,Stephen M. Watt +1 more
TL;DR: This paper presents another approach for real-time recognition: certain characteristics of a curve can be computed as the curve is being written, and these characteristics are used to classify the character in constant time when the pen is lifted.
Proceedings ArticleDOI
Online computation of similarity between handwritten characters
Oleg Golubitsky,Stephen M. Watt +1 more
TL;DR: It is concluded that the Legendre-Sobolev distance measure provides a competitive alternative to elastic matching, being almost as accurate and much faster than elastic matching.