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Proceedings Paper

Improving isolated and in-context classication of handwritten characters
Author(s): Vadim Mazalov; Stephen M. Watt
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Paper Abstract

Earlier work has shown how to recognize handwritten characters by representing coordinate functions or integral invariants as truncated orthogonal series. The series basis functions are orthogonal polynomials defined by a Legendre-Sobolev inner product. It has been shown that the free parameter in the inner product, the 'jet scale', has an impact on recognition both using coordinate functions and integral invariants. This paper develops methods of improving series-based recognition. For isolated classification, the first consideration is to identify optimal values for the jet scale in different settings. For coordinate functions, we find the optimum to be in a small interval with the precise value not strongly correlated to the geometric complexity of the character. For integral invariants, used in orientation-independent recognition, we find the optimal value of the jet scale for each invariant. Furthermore, we examine the optimal degree for the truncated series. For in-context classification, we develop a rotation-invariant algorithm that takes advantage of sequences of samples that are subject to similar distortion. The algorithm yields significant improvement over orientation-independent isolated recognition and can be extended to shear and, more generally, affine transformations.

Paper Details

Date Published: 24 January 2012
PDF: 8 pages
Proc. SPIE 8297, Document Recognition and Retrieval XIX, 82970B (24 January 2012); doi: 10.1117/12.912112
Show Author Affiliations
Vadim Mazalov, The Univ. of Western Ontario (Canada)
Stephen M. Watt, The Univ. of Western Ontario (Canada)


Published in SPIE Proceedings Vol. 8297:
Document Recognition and Retrieval XIX
Christian Viard-Gaudin; Richard Zanibbi, Editor(s)

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