Generalizing edit distance for handwritten text recognition

Giovanni Seni; V. Kripasundar; Rohini K. Srihari

doi:10.1117/12.205841

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30 March 1995 Generalizing edit distance for handwritten text recognition

Giovanni Seni, V. Kripasundar, Rohini K. Srihari

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Proceedings Volume 2422, Document Recognition II; (1995) https://doi.org/10.1117/12.205841
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

In this paper the Damerau-Levenshtein string difference metric is generalized in two ways to more accurately compensate for the types of errors that are present in the script recognition domain. First, the basic dynamic programming method for computing such a measure is extended to allow for merges, splits and two-letter substitutions. Second, edit operations are refined into categories according to the effect they have on the visual `appearance' of words. A set of recognizer-independent constraints is developed to reflect the severity of the information lost due to each operation. These constraints are solved to assign specific costs to the operations. Experimental results on 2,335 corrupted strings and a lexicon of 21,299 words show higher correcting rates than with the original form.

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Giovanni Seni, V. Kripasundar, and Rohini K. Srihari "Generalizing edit distance for handwritten text recognition", Proc. SPIE 2422, Document Recognition II, (30 March 1995); https://doi.org/10.1117/12.205841

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