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Titolo:
An overview of character recognition focused on off-line handwriting
Autore:
Arica, N; Yarman-Vural, FT;
Indirizzi:
Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey Middle E Tech Univ Ankara Turkey TR-06531 Engn, TR-06531 Ankara, Turkey
Titolo Testata:
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
fascicolo: 2, volume: 31, anno: 2001,
pagine: 216 - 233
SICI:
1094-6977(200105)31:2<216:AOOCRF>2.0.ZU;2-R
Fonte:
ISI
Lingua:
ENG
Soggetto:
PARALLEL THINNING ALGORITHMS; CURSIVE SCRIPT RECOGNITION; HIDDEN MARKOV-MODELS; WORD RECOGNITION; PATTERN-RECOGNITION; CHINESE-CHARACTERS; DIGIT RECOGNITION; NEURAL NETWORKS; HANDPRINTED CHARACTERS; AUTOMATIC RECOGNITION;
Keywords:
character recognition (CR); feature extraction; off-line handwriting recognition; segmentation; training and recognition;
Tipo documento:
Review
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
191
Recensione:
Indirizzi per estratti:
Indirizzo: Arica, N Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey Middle E Tech Univ Ankara Turkey TR-06531 -06531 Ankara, Turkey
Citazione:
N. Arica e F.T. Yarman-Vural, "An overview of character recognition focused on off-line handwriting", IEEE SYST C, 31(2), 2001, pp. 216-233

Abstract

Character recognition (CR) has been extensively studied in the last half century and progressed to a level sufficient to produce technology driven applications. Now, the rapidly growing computational power enables the implementation of the present CR methodologies and creates an increasing demand on many emerging application domains, which require more advanced methodologies. This material serves as a guide and update for readers working in the CR area. First, the historical evolution of CR systems is presented. Then, the available CR techniques with their superiorities and weaknesses are reviewed. Finally, the current status of CR is discussed, and directions for future research are suggested. Special attention is given to the off-line handwriting recognition since this area requires more research to reach the ultimate goal of machine simulation of human reading.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/03/20 alle ore 08:38:22