TY - GEN
T1 - Recent approaches in online handwriting recognition for Persian and Arabic right-to-left languages
AU - Alipour, Sanaz Adel
AU - Tabatabaey-Mashadi, Narges
AU - Abbassi, Hassan
N1 - © 2016 IEEE.
PY - 2017/5/10
Y1 - 2017/5/10
N2 - Online handwriting recognition redefined along the rapid change of technology which began to replace keyboards with digital pen and tablets. However compared to English letter-based languages, less attention is paid to right-to-left languages especially Persian and Arabic. The complex nature of cursive writing in these languages acquires elaborate methods to simultaneously take speed, accuracy and complexity into account. This paper overviews the up-to-date efforts put into online Persian and Arabic handwriting recognition. Through this paper word/stroke-based and segment-based methods are discussed. Additionally template based recognition algorithms and artificial intelligent approaches are explained with respect to dictionary check requirements and benchmark databases. Real-time online handwriting recognition of such languages is another recent field of interest that is researched for potentially practical methods.
AB - Online handwriting recognition redefined along the rapid change of technology which began to replace keyboards with digital pen and tablets. However compared to English letter-based languages, less attention is paid to right-to-left languages especially Persian and Arabic. The complex nature of cursive writing in these languages acquires elaborate methods to simultaneously take speed, accuracy and complexity into account. This paper overviews the up-to-date efforts put into online Persian and Arabic handwriting recognition. Through this paper word/stroke-based and segment-based methods are discussed. Additionally template based recognition algorithms and artificial intelligent approaches are explained with respect to dictionary check requirements and benchmark databases. Real-time online handwriting recognition of such languages is another recent field of interest that is researched for potentially practical methods.
KW - Online handwriting recognition
KW - Real time handwriting recognition
KW - Right-to-left language
KW - Segment-based
KW - Word-based
UR - http://www.scopus.com/inward/record.url?scp=85020180603&partnerID=8YFLogxK
U2 - 10.1109/CompComm.2016.7924723
DO - 10.1109/CompComm.2016.7924723
M3 - Conference contribution
AN - SCOPUS:85020180603
T3 - 2016 2nd IEEE International Conference on Computer and Communications, ICCC 2016 - Proceedings
SP - 358
EP - 364
BT - 2016 2nd IEEE International Conference on Computer and Communications, ICCC 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
CY - New Jersey, United States
T2 - 2nd IEEE International Conference on Computer and Communications, ICCC 2016
Y2 - 14 October 2016 through 17 October 2016
ER -