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On-line and Off-line Handwriting Recognition: A Comprehensive Survey
| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Citations: | 494 - 8 self |
BibTeX
@ARTICLE{Plamondon_on-lineand,
author = {Reâ Jean Plamondon and Sargur N. Srihari},
title = {On-line and Off-line Handwriting Recognition: A Comprehensive Survey},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {},
pages = {63--84}
}
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Abstract
AbstractÐHandwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a PDA, in postal addresses on envelopes, in amounts in bank checks, in handwritten fields in forms, etc. This overview describes the nature of handwritten language, how it is transduced into electronic data, and the basic concepts behind written language recognition algorithms. Both the on-line case (which pertains to the availability of trajectory data during writing) and the off-line case (which pertains to scanned images) are considered. Algorithms for preprocessing, character and word recognition, and performance with practical systems are indicated. Other fields of application, like signature verification, writer authentification, handwriting learning tools are also considered.
Keyphrases
comprehensive survey off-line handwriting recognition word recognition abstract handwriting trajectory data postal address machine recognition signature verification human transaction practical system off-line case new technology day-to-day life learning tool basic concept practical significance language recognition algorithm handwritten language writer authentification electronic data handwritten note handwritten field on-line case bank check
