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Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Verifying the UNIPEN Devset
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
Louis Vuurpijl, Nijmegen Institute for Cognition and Information
Ralph Niels, Nijmegen Institute for Cognition and Information
Merijn van Erp, Nijmegen Institute for Cognition and Information
Lambert Schomaker, University of Groningen
Eugene Ratzlaff, IBM Research
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.
Citation:
Louis Vuurpijl, Ralph Niels, Merijn van Erp, Lambert Schomaker, Eugene Ratzlaff, "Verifying the UNIPEN Devset," iwfhr, pp.586-591, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
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