On-line handwriting character recognition algorithm RAV (reparameterized angle variations)

S. Masaki; M. Kobayashi; O. Miyamoto; Y. Nakagawa; T. Matsumoto

On-line handwriting character recognition algorithm RAV (reparameterized angle variations)

S. Masaki^*, M. Kobayashi, O. Miyamoto, Y. Nakagawa, T. Matsumoto

^*Corresponding author for this work

School of Advanced Science and Engineering

Research output: Contribution to conference › Paper › peer-review

10 Citations (Scopus)

Abstract

A new algorithm RAV (Reparameterized Angle Variations) is proposed which makes explicit use of trajectory information where the time evolution of the pen coordinates plays a crucial role. The algorithm is extremely robust against stroke connections (`Tsuzuke-ji') as well as shape distortions (`Kuzushi-ji'). Preliminary experiments are reported on tests against the Kuchibue_d-96-02 data base from Tokyo University of Agriculture and Technology.

Original language	English
Pages	919-925
Number of pages	7
Publication status	Published - 1997 Jan 1
Event	Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) - Ulm, Ger Duration: 1997 Aug 18 → 1997 Aug 20

Other

Other	Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2)
City	Ulm, Ger
Period	97/8/18 → 97/8/20

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Cite this

@conference{03b3a68c68df4d07a304996dd3fe3988,

title = "On-line handwriting character recognition algorithm RAV (reparameterized angle variations)",

abstract = "A new algorithm RAV (Reparameterized Angle Variations) is proposed which makes explicit use of trajectory information where the time evolution of the pen coordinates plays a crucial role. The algorithm is extremely robust against stroke connections (`Tsuzuke-ji') as well as shape distortions (`Kuzushi-ji'). Preliminary experiments are reported on tests against the Kuchibue_d-96-02 data base from Tokyo University of Agriculture and Technology.",

author = "S. Masaki and M. Kobayashi and O. Miyamoto and Y. Nakagawa and T. Matsumoto",

year = "1997",

month = jan,

day = "1",

language = "English",

pages = "919--925",

note = "Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) ; Conference date: 18-08-1997 Through 20-08-1997",

}

TY - CONF

T1 - On-line handwriting character recognition algorithm RAV (reparameterized angle variations)

AU - Masaki, S.

AU - Kobayashi, M.

AU - Miyamoto, O.

AU - Nakagawa, Y.

AU - Matsumoto, T.

PY - 1997/1/1

Y1 - 1997/1/1

N2 - A new algorithm RAV (Reparameterized Angle Variations) is proposed which makes explicit use of trajectory information where the time evolution of the pen coordinates plays a crucial role. The algorithm is extremely robust against stroke connections (`Tsuzuke-ji') as well as shape distortions (`Kuzushi-ji'). Preliminary experiments are reported on tests against the Kuchibue_d-96-02 data base from Tokyo University of Agriculture and Technology.

AB - A new algorithm RAV (Reparameterized Angle Variations) is proposed which makes explicit use of trajectory information where the time evolution of the pen coordinates plays a crucial role. The algorithm is extremely robust against stroke connections (`Tsuzuke-ji') as well as shape distortions (`Kuzushi-ji'). Preliminary experiments are reported on tests against the Kuchibue_d-96-02 data base from Tokyo University of Agriculture and Technology.

UR - http://www.scopus.com/inward/record.url?scp=0030649988&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030649988&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0030649988

SP - 919

EP - 925

T2 - Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2)

Y2 - 18 August 1997 through 20 August 1997

ER -

On-line handwriting character recognition algorithm RAV (reparameterized angle variations)

Abstract

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this