an Integration of Online And Pseudo-Online Information for Cursive Word Recognition
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An Integration of Online and Pseudo-Online Information for Cursive Word Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., 27(5):669-683, 2005
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Abstract
In this paper, we present a novel method to extract stroke order independent information from online data. This information, which we term pseudo-online, conveys relevant information on the offline representation of the word. Based on this information, a combination of classification decisions from online and pseudo-online cursive word recognizers is performed to improve the recognition of online cursive words. One of the most valuable aspects of this approach with respect to similar methods that combine online and offline classifiers for word recognition is that the pseudo-online representation is similar to the online signal and, hence, word recognition is based on a single engine. Results demonstrate that the pseudo-online representation is useful as the combination of classifiers perform better than those based solely on pure online information.
Keywords
Co-authors
Bibtex Entry
@article{SteinherzRIN05a,
title = {An Integration of Online and Pseudo-Online Information for Cursive Word Recognition.},
author = {Tal Steinherz and Ehud Rivlin and Nathan Intrator and Predrag Neskovic},
year = {2005},
journal = {IEEE Trans. Pattern Anal. Mach. Intell.},
volume = {27},
number = {5},
pages = {669-683},
keywords = {Online, offline, handwriting, cursive, word recognition, classifier combination.},
abstract = {In this paper, we present a novel method to extract stroke order independent information from online data. This information, which we term pseudo-online, conveys relevant information on the offline representation of the word. Based on this information, a combination of classification decisions from online and pseudo-online cursive word recognizers is performed to improve the recognition of online cursive words. One of the most valuable aspects of this approach with respect to similar methods that combine online and offline classifiers for word recognition is that the pseudo-online representation is similar to the online signal and, hence, word recognition is based on a single engine. Results demonstrate that the pseudo-online representation is useful as the combination of classifiers perform better than those based solely on pure online information.}
}