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25 June 1999 Stochastic model of handwritten letters and words to simulate and recognize handwriting
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Abstract
Among the many handwritten character recognition algorithms that have been proposed, few of them use models which are able to simulate handwriting. This can be explained by the fact that simulations require the estimation of strokes starting form statistic imags of letters, while crossing and overlapping strokes make this estimation difficult. In this paper an algorithm to extract overlapping strokes that optimizes the reconstruction of crossings of the image is describes, and a stochastic model of off-line handwritten letter deformation for handwritten letter recognition is presented.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric L'Homer "Stochastic model of handwritten letters and words to simulate and recognize handwriting", Proc. SPIE 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems, (25 June 1999); https://doi.org/10.1117/12.351305
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