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