Markov Models for Handwriting Recognition
Since their first inception more than half a century ago, automatic reading systems have evolved substantially, thereby showing impressive performance on machine-printed text. The recognition of handwriting can, however, still be considered an open resear
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Thomas Plötz Gernot A. Fink •
Markov Models for Handwriting Recognition
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Dr. Thomas Plötz Culture Lab School of Computing Science Newcastle University Grand Assembly Rooms, King’s Walk Newcastle upon Tyne NE1 7RU UK e-mail: [email protected]
ISSN 2191-5768 ISBN 978-1-4471-2187-9 DOI 10.1007/978-1-4471-2188-6
Prof. Dr. Gernot A. Fink Department of Computer Science Technische Universität Dortmund Otto-Hahn-Strasse 16 44227 Dortmund Germany e-mail: [email protected]
e-ISSN 2191-5776 e-ISBN 978-1-4471-2188-6
Springer London Dordrecht Heidelberg New York British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Ó Thomas Plötz 2011 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover design: eStudio Calamar, Berlin/Figueres Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The history of the development of Markov model-based pattern recognition methods is closely related to the field of automatic speech recognition. There, hidden Markov models and related techniques were developed from their infancy into a mature framework for the analysis of sequential data. Not before the 1990s researchers who were working on speech recognition before transferred the technology to the field of optical character recognition with a special focus on handwritten script. In much the same way the authors of this book made their way from spoken language technology to handwriting recognition research. It started with a project lead by Gernot A. Fink and Gerhard Sagerer at Bielefeld University, Germany, which focussed on camera-based handwriting recognition and first addressed the task of reading handwritten notes on a whiteboard. This research initiative resulted in a successor project lead by the authors at TU Dortmund, Germany, which aimed at a more thorough investigation of the problem of c
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