article

Handwritten Chinese text editing and recognition system

Authors:

Xiaolong WangAuthors Info & Claims

Multimedia Tools and Applications, Volume 71, Issue 3

Pages 1363 - 1380

https://doi.org/10.1007/s11042-012-1270-2

Published: 01 August 2014 Publication History

Abstract

This paper describes a handwritten Chinese text editing and recognition system that can edit handwritten text and recognize it with a client-server mode. First, the client end samples and redisplays the handwritten text by using digital ink technics, segments handwritten characters, edits them and saves original handwritten information into a self-defined document. The self-defined document saves coordinates of all sampled points of handwriting characters. Second, the server recognizes handwritten document based on the proposed Gabor feature extraction and affinity propagation clustering (GFAP) method, and returns the recognition results to client end. Moreover, the server can also collect the labeled handwritten characters and fine tune the recognizer automatically. Experimental results on HIT-OR3C database show that our handwriting recognition method improves the recognition performance remarkably.

References

[1]

Avola D, Caschera MC, Ferri F, Grifoni P (2010) Classifying and resolving ambiguities in sketch based interaction. Int J Virt Tech Multimed 1(2):104---139

Digital Library

[2]

Ding K, Jin L, Liu G, Gao J, Mei Z (2011) Incremental learning of mqdf for writer adaptation. ICIC-EL, Part B: Applications 2:25---30

[3]

Frey BJ, Dueck D (2007) Clustering by passing messages between data points. Science 315(5814):972---976

[4]

Holzinger A, Schloegl M, Peischl B, Debevc M (2010) Preferences of handwriting recognition on mobile information systems in medicine: improving handwriting algorithm on the basis of real-life usability research. In: International joint conference on e-business and telecommunications, 26---28 Jul 2010. IEEE, Athens, pp 120---123

[5]

Holzinger A, Basic L, Peischl B, Debevc M (2011) Handwriting recognition on mobile devices: state of the art technology, usability and business analysis. In: International conference on electronic business and telecommunications, 18---21 Jul 2011. Springer, Seville, Spain, pp 219---227

[6]

Holzinger A, Schloegl M, Peischl B, Debevc M (2012) Optimization of a handwriting recognition algorithm for a mobile enterprise health information system on the basis of real-life usability research. CCIS 222:97---111

[7]

Huang Z, Ding K, Jin L, Gao X (2009) Writer adaptive online handwriting recognition using incremental linear discriminant analysis. In: International Conference on Document Analysis and Recognition, 26---29 Jul 2009. IEEE, Barcelona, Spain, pp 91---95

[8]

Jin L, Ding K, Huang Z (2010) Incremental learning of lda model for chinese writer adaptation. Neurocomputing 73(10---12):1614---1623

[9]

Jin LW, Gao Y, Liu G, Li YY, Ding K (2011) Scut-couch2009-a comprehensive online unconstrained chinese handwriting database and benchmark evaluation. Int J Doc Anal Recognit 14(1):53---64

Digital Library

[10]

Kim IJ, Kim JH (2003) Statistical character structure modeling and its application to handwritten chinese character recognition. IEEE Trans Pattern Anal Mach Intell 25(11):1422---1436

Digital Library

[11]

Kimura F, Takashina K, Tsuruoka S, Miyake Y (1987) Modified quadratic discriminant functions and the application to chinese character-recognition. IEEE Trans Pattern Anal Mach Intell 9(1):149---153

Digital Library

[12]

Liu CL, Marukawa K (2005) Pseudo two-dimensional shape normalization methods for handwritten chinese character recognition. Pattern Recogn 38(12):2242---2255

Digital Library

[13]

Liu CL, Zhou XD (2006) Online japanese character recognition using trajectory-based normalization and direction feature extraction. In: International Workshop on Frontiers in Handwriting Recognition, 23---26 Oct 2006. Suvisoft, La Baule, France, pp 217---222

[14]

Liu CL, Jaeger S, Nakagawa M (2004) Online recognition of chinese characters: the state-of-the-art. IEEE Trans Pattern Anal Mach Intell 26(2):198---213

Digital Library

[15]

Liu CL, Nakashima K, Sako H, Fujisawa H (2004) Handwritten digit recognition: investigation of normalization and feature extraction techniques. Pattern Recogn 37(2):265---279

[16]

Long T, Jin L (2008) A novel orientation free method for online unconstrained cursive handwritten chinese word recognition. In: International Conference on Pattern Recognition, 4---6 Dec 2008. IEEE, Orlando, Florida, USA, pp 1---4

[17]

Long T, Jin LW (2008) Building compact mqdf classifier for large character set recognition by subspace distribution sharing. Pattern Recogn 41(9):2916---2925

Digital Library

[18]

Plamondon R, Srihari SN (2000) Online and off-line handwriting recognition: a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 22(1):63---84

Digital Library

[19]

Wang DH, Liu CL, Yu J, Zhou XD (2009) Casia-olhwdb1: a database of online handwritten chinese characters. In: International conference on document analysis and recognition, 26---29 Jul 2009. IEEE, Barcelona, Spain, pp 1206---1210

[20]

Wang QF, Yin F, Liu CL (2009) Integrating language model in handwritten chinese text recognition. In: International conference on document analysis and recognition, 26---29 Jul 2009. IEEE, Barcelona, Spain, pp 1036---1040

[21]

Wang XW, Ding XQ, Liu CS (2005) Gabor filters-based feature extraction for character recognition. Pattern Recogn 38(3):369---379

Digital Library

[22]

Welling M (2006) Fisher linear discriminant analysis. Tech. rep., Department of Computer Science, University of Toronto

[23]

Wu T, Ma S (2003) Feature extraction by hierarchical overlapped elastic meshing for handwritten chinese character recognition. In: International conference on document analysis and recognition, 3---6 Aug 2003. IEEE, Edinburgh, Scotland, UK, pp 529---533

[24]

Zhang HP, Yu HK, Xiong DY, Liu Q (2003) Hhmm-based chinese lexical analyzer ictclas. In: SIGHAN workshop on Chinese language processing, 11---12 Jul 2003. ACM, Sapporo, Japan, pp 184---187

[25]

Zhang P, Bui TD, Suen CY (2007) A novel cascade ensemble classifier system with a high recognition performance on handwritten digits. Pattern Recogn 40(12):3415---3429

Digital Library

[26]

Zhao SY, Chi ZR, Shi PF, Yan H (2003) Two-stage segmentation of unconstrained handwritten chinese characters. Pattern Recogn 36(1):145---156

[27]

Zhou S, Chen Q, Wang X (2010) Hit-or3c: An opening recognition corpus for chinese characters. In: International workshop on document analysis systems, 9---11 June 2010. ACM, Boston, MA, USA, pp 223---230

Cited By

Nurseitov DBostanbekov KKurmankhojayev DAlimova AAbdallah ATolegenov R(2021)Handwritten Kazakh and Russian (HKR) database for text recognitionMultimedia Tools and Applications10.1007/s11042-021-11399-680:21-23(33075-33097)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s11042-021-11399-6

Handwritten Chinese text editing and recognition system
1. Applied computing
  1. Document management and text processing
    1. Document capture
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning

Recommendations

Offline arabic handwritten text recognition: A Survey

Research in offline Arabic handwriting recognition has increased considerably in the past few years. This is evident from the numerous research results published recently in major journals and conferences in the area of handwriting recognition. Features ...
Stroke Segmentation and Recognition from Bangla Online Handwritten Text
ICFHR '12: Proceedings of the 2012 International Conference on Frontiers in Handwriting Recognition

This paper deals with recognition of online handwritten Bangla (Bengali) text. Here, at first, we segment cursive words into strokes. A stroke may represent a character or a part of a character. We selected a set of Bangla words written by different ...
Offline handwritten Amharic word recognition

This paper describes two approaches for Amharic word recognition in unconstrained handwritten text using HMMs. The first approach builds word models from concatenated features of constituent characters and in the second method HMMs of constituent ...

Comments

Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 71, Issue 3

August 2014

1055 pages

ISSN:1380-7501

Issue’s Table of Contents

Copyright © Copyright © 2014 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 August 2014

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Nurseitov DBostanbekov KKurmankhojayev DAlimova AAbdallah ATolegenov R(2021)Handwritten Kazakh and Russian (HKR) database for text recognitionMultimedia Tools and Applications10.1007/s11042-021-11399-680:21-23(33075-33097)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s11042-021-11399-6

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents