Generalizing Edit Distance To Incorporate Domain Information: Handwritten text recognition as a case study

Generalizing Edit Distance To Incorporate Domain Information: Handwritten text recognition as a case study (1996)

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by Giovanni Seni , V Kripasundar , V Krip Asundar , Rohini K. Srihari

Venue:	Pattern Recognition
Citations:	8 - 0 self

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Datum	Value	Source
TITLE	Generalizing Edit Distance To Incorporate Domain Information: Handwritten text recognition as a case study	user correction - Legacy Corrections
AUTHOR NAME	Giovanni Seni	user correction - Legacy Corrections
AUTHOR AFFIL	CEDAR/SUNY at Buffalo	user correction - Legacy Corrections
AUTHOR ADDR	226 Bell Hall; Buffalo, NY 14260	user correction - Legacy Corrections
AUTHOR NAME	V Kripasundar	user correction - Legacy Corrections
AUTHOR NAME	V Krip Asundar	user correction - Legacy Corrections
AUTHOR AFFIL	CEDAR/SUNY at Buffalo	user correction - Legacy Corrections
AUTHOR ADDR	226 Bell Hall; Buffalo, NY 14260	user correction - Legacy Corrections
AUTHOR NAME	Rohini K. Srihari	user correction - Legacy Corrections
AUTHOR AFFIL	CEDAR/SUNY at Buffalo	user correction - Legacy Corrections
AUTHOR ADDR	226 Bell Hall; Buffalo, NY 14260	user correction - Legacy Corrections
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. Keywords: string distance, string matching, spelling error correction, word recognition and correction, text editing, script recognition and post-processing 1 INTRODUCTION Since the goal of text recog...	user correction - Legacy Corrections
YEAR	1996	INFERENCE
VENUE	Pattern Recognition	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
VOLUME	29	INFERENCE
CITATIONS	15 found	ParsCit 1.0