Offline Cursive Script Word Recognition - a Survey
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Offline cursive script word recognition - a survey.
IJDAR, 2(2-3):90-110, 1999
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Abstract
We review the field of offline cursive word recognition. We mainly deal with the various methods that were proposed to realize the core of recognition in a word recognition system. These methods are discussed in view of the two most important properties of such a system: the size and nature of the lexicon involved, and whether or not a segmentation stage is present. We classify the field into three categories: segmentation-free methods, which compare a sequence of observations de- rived from a word image with similar references of words in the lexicon; segmentation-based methods, that look for the best match between consecutive sequences of primitive segments and letters of a possible word; and the perception-oriented approach, that relates to methods that perform a human-like reading technique, in which anchor features found all over the word are used to boot- strap a few candidates for a final evaluation phase.
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Bibtex Entry
@article{SteinherzRI99a,
title = {Offline cursive script word recognition - a survey.},
author = {Tal Steinherz and Ehud Rivlin and Nathan Intrator},
year = {1999},
journal = {IJDAR},
volume = {2},
number = {2-3},
pages = {90-110},
keywords = {Offline; Cursive; Handwritten; Word recognition; Segmentation; Survey},
abstract = {We review the field of offline cursive word recognition. We mainly deal with the various methods that were proposed to realize the core of recognition in a word recognition system. These methods are discussed in view of the two most important properties of such a system: the size and nature of the lexicon involved, and whether or not a segmentation stage is present. We classify the field into three categories: segmentation-free methods, which compare a sequence of observations de- rived from a word image with similar references of words in the lexicon; segmentation-based methods, that look for the best match between consecutive sequences of primitive segments and letters of a possible word; and the perception-oriented approach, that relates to methods that perform a human-like reading technique, in which anchor features found all over the word are used to boot- strap a few candidates for a final evaluation phase.}
}