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Proceedings Paper

Conformal mapping-based hand-written word and sentence representation and recognition
Author(s): Dalila B. Megherbi; Yohannes Iyassu; A. J. Boulenouar
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Paper Abstract

In this paper, we introduce a technique for handwritten words and sentences representation and recognition. The proposed method is based on complex variables and conformal mapping methodology. In particular, in a previous work, through a complex variable methodology and conformal mapping process, we demonstrated the ability to recognized shapes and concisely represent shape boundaries using a set of polynomial coefficients derived in the mapping process. In this work we illustrate how these previous results can be applied to hand-written words and sentences. We show that the words/sentences classification techniques used are adapted to the feature-coefficients selected and are based on feature-coefficients similarities in combination with the minimum distance classifier. We use as measures the Euclidean distance as well as the covariance matrix eigen- values distance. Finally, experimental results of handwritten words and sentences are shown to show the power, versatility and robustness of the proposed technique.

Paper Details

Date Published: 28 August 2001
PDF: 9 pages
Proc. SPIE 4388, Visual Information Processing X, (28 August 2001);
Show Author Affiliations
Dalila B. Megherbi, Univ. of Massachusetts/Lowell (United States)
Yohannes Iyassu, Univ. of Massachusetts/Lowell (United States)
A. J. Boulenouar, Univ. of Massachusetts/Lowell (United States)

Published in SPIE Proceedings Vol. 4388:
Visual Information Processing X
Stephen K. Park; Zia-ur Rahman; Robert A. Schowengerdt, Editor(s)

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