Handwriting recognition

Soft computing and probabilistic approaches

Zhi-Qiang Liu, Jinhai Cai, Richard Buse

246 pages, parution le 28/07/2003

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Résumé

This book takes a fresh look at the problem of unconstrained handwriting recognition and introduces the reader to new techniques for the recognition of written words and characters using statistical and soft computing approaches. The types of uncertainties and variations present in handwriting data are discussed in detail. The book presents several algorithms that use modified hidden Markov models and Markov random field models to model the handwriting data statistically and structurally in a single framework. The book explores methods that use fuzzy logic and fuzzy sets for handwriting recognition. The effectiveness of these techniques is demonstrated through extensive experimental results and real handwritten characters and words.

Introduction
Pre-processing and feature extraction
Hidden Markov model-based method for recognizing hand-written digits
Markov models with spectral features for handwritten numeral recognition
Markov random field model for recognizing handwritten digits
Markov random field model for recognizing handwritten words
A structural and relational approach to handwritten word recognition
Handwritten word recognition using fuzzy logic
Conclusion

Index

L'auteur - Zhi-Qiang Liu

Liu, Z.-Q., City University of Hong Kong, China

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Zhi-Qiang Liu, Jinhai Cai, Richard Buse
Parution	28/07/2003
Nb. de pages	246
Format	16 x 24
Couverture	Relié
Poids	480g
Intérieur	Noir et Blanc
EAN13	9783540401773