Paper
23 January 2012 Improving isolated and in-context classication of handwritten characters
Vadim Mazalov, Stephen M. Watt
Author Affiliations +
Proceedings Volume 8297, Document Recognition and Retrieval XIX; 82970B (2012) https://doi.org/10.1117/12.912112
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vadim Mazalov and Stephen M. Watt "Improving isolated and in-context classication of handwritten characters", Proc. SPIE 8297, Document Recognition and Retrieval XIX, 82970B (23 January 2012); https://doi.org/10.1117/12.912112
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Algorithm development

Distortion

Mathematics

Classification systems

Error analysis

Optical character recognition

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