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This book offers a novel perspective on unconstrained handwriting recognition, introducing advanced techniques for identifying written words and characters. It delves into the complexities of uncertainties and variations inherent in handwriting data. The text presents algorithms that employ modified hidden Markov models and Markov random field models to statistically and structurally represent handwriting within a unified framework. Methods utilizing fuzzy logic and fuzzy sets for recognition are also explored, with their efficacy validated through extensive experimental data.