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Ninth International Workshop on Frontiers in Handwriting Recognition (2004)
Kokubunji, Tokyo, Japan
Oct. 26, 2004 to Oct. 29, 2004
ISSN: 1550-5235
ISBN: 0-7695-2187-8
pp: 586-591
Louis Vuurpijl , Nijmegen Institute for Cognition and Information
Merijn van Erp , Nijmegen Institute for Cognition and Information
Lambert Schomaker , University of Groningen
Ralph Niels , Nijmegen Institute for Cognition and Information
Eugene Ratzlaff , IBM Research
ABSTRACT
This paper describes a semi-automated procedure for the verification of a large human-labeled data set containing online handwriting. A number of classifiers trained on the UNIPEN "trainset" is employed for detecting anomalies in the labels of the UNIPEN "devset". Multiple classifiers with different feature sets are used to increase the robustness of the automated procedure and to ensure that the number of false accepts is kept to a minimum. The rejected samples are manually categorized into four classes: (i) recoverable segmentation errors, (ii) incorrect (recoverable) labels, (iii) well-segmented but ambiguous cases and (iv) unrecoverable segments that should be removed. As a result of the verification procedure, a well-labeled data set is currently being generated, which will be made available to the handwriting recognition community.
INDEX TERMS
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CITATION
Louis Vuurpijl, Merijn van Erp, Lambert Schomaker, Ralph Niels, Eugene Ratzlaff, "Verifying the UNIPEN Devset", Ninth International Workshop on Frontiers in Handwriting Recognition, vol. 00, no. , pp. 586-591, 2004, doi:10.1109/IWFHR.2004.109
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