Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach

Cheng CHENG; Bilan ZHU; Masaki NAKAGAWA

doi:10.1587/transinf.E96.D.681

Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach

Cheng CHENG, Bilan ZHU, Masaki NAKAGAWA

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This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching.

Publication: IEICE TRANSACTIONS on Information Vol.E96-D No.3 pp.681-689

Publication Date: 2013/03/01

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Online ISSN: 1745-1361

DOI: 10.1587/transinf.E96.D.681

Type of Manuscript: PAPER

Category: Pattern Recognition

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Cheng CHENG, Bilan ZHU, Masaki NAKAGAWA, "Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach" in IEICE TRANSACTIONS on Information, vol. E96-D, no. 3, pp. 681-689, March 2013, doi: 10.1587/transinf.E96.D.681.
Abstract: This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E96.D.681/_p

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@ARTICLE{e96-d_3_681,
author={Cheng CHENG, Bilan ZHU, Masaki NAKAGAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach},
year={2013},
volume={E96-D},
number={3},
pages={681-689},
abstract={This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching.},
keywords={},
doi={10.1587/transinf.E96.D.681},
ISSN={1745-1361},
month={March},}

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TY - JOUR
TI - Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach
T2 - IEICE TRANSACTIONS on Information
SP - 681
EP - 689
AU - Cheng CHENG
AU - Bilan ZHU
AU - Masaki NAKAGAWA
PY - 2013
DO - 10.1587/transinf.E96.D.681
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2013
AB - This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching.
ER -