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    RECOGNITION OF WHITEBOARD NOTES
    Online, Offline and Combination

    by Marcus Liwicki (DFKI GmbH, Germany) & Horst Bunke (University of Bern, Switzerland)

    Table of Contents (73k)
    Preface (57k)
    Chapter 1: Introduction (652k)

    This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.

    The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.

     
    Contents:
    • Classification Methods
    • Linguistic Resources and Handwriting Databases
    • Off-Line Approach
    • On-Line Approach
    • Multiple Classifier Combination
    • Writer-Dependent Recognition
     
    Readership: Researchers in academia and industry and graduate students working in document analysis, handwriting recognition, pattern recognition, and artificial intelligence.
     


     
    228pp    Pub. date: Sep 2008  
    ISBN:   978-981-281-453-1
    981-281-453-1
       US$90 / £52

     


    228pp    Pub. date: Sep 2008  
    ISBN:   978-981-281-454-8(ebook)
    981-281-454-X(ebook)
       US$116 / £68

     


     

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    Updated on 20 November 2009