Conformal mapping-based hand-written word and sentence representation and recognition

Dalila B. Megherbi; Yohannes Iyassu; A. J. Boulenouar

doi:10.1117/12.438264

28 August 2001 Conformal mapping-based hand-written word and sentence representation and recognition

Dalila B. Megherbi, Yohannes Iyassu, A. J. Boulenouar

Proceedings Volume 4388, Visual Information Processing X; (2001) https://doi.org/10.1117/12.438264
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

Citation Download Citation

Dalila B. Megherbi, Yohannes Iyassu, and A. J. Boulenouar "Conformal mapping-based hand-written word and sentence representation and recognition", Proc. SPIE 4388, Visual Information Processing X, (28 August 2001); https://doi.org/10.1117/12.438264

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KEYWORDS

Distance measurement

Object recognition

Pattern recognition

Databases

Detection and tracking algorithms

Algorithm development

Associative arrays

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