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Comparative performance analysis of stroke correspondence search methods for stroke-order free online multi-stroke character recognition

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Abstract

For stroke-order free online multi-stroke character recognition, stroke-to-stroke correspondence search between an input pattern and a reference pattern plays an important role to deal with the stroke-order variation. Although various methods of stroke correspondence have been proposed, no comparative study for clarifying the relative superiority of those methods has been done before. In this paper, we firstly review the approaches for solving the stroke-order variation problem. Then, five representative methods of stroke correspondence proposed by different groups, including cube search (CS), bipartite weighted matching (BWM), individual correspondence decision (ICD), stable marriage (SM), and deviation-expansion model (DE), are experimentally compared, mainly in regard of recognition accuracy and efficiency. The experimental results on an online Kanji character dataset, showed that 99.17%, 99.17%, 96.37%, 98.54%, and 96.59% were attained by CS, BWM, ICD, SM, and DE, respectively as their recognition rates. Extensive discussions are made on their relative superiorities and practicalities.

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Authors and Affiliations

  1. Department of Advanced Information Technology, Kyushu University, Fukuoka-shi, 819-0395, Japan

    Wenjie Cai, Seiichi Uchida & Hiroaki Sakoe

Authors
  1. Wenjie Cai
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  2. Seiichi Uchida
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  3. Hiroaki Sakoe
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Corresponding author

Correspondence to Wenjie Cai.

Additional information

Wenjie Cai received BE and ME degrees from Wuhan University, China in 1990 and 1996, respectively, and PhD degree from Kyushu University, Japan in 2012. From April 2007, he has been working at O-RID company, Japan. His research interests include character recognition and image processing. He is a member of the IEEE Computer Society.

Seiichi Uchida received BE, ME, and PhD degrees from Kyushu University in 1990, 1992, and 1999, respectively. From 1992 to 1996, he joined SECOMCo., Ltd., Tokyo, Japan where he worked on speech processing. Currently, he is a professor at Faculty of Information Science and Electrical Engineering, Kyushu University. His research interests include pattern recognition and image processing. He received 2002 IEICE PRMU Research Encouraging Award, MIRU2006 Nagao Award (best paper award), 2007 IAPR/ICDAR Best Paper Award, and 2009 IEICE Best Paper Award. Dr. Uchida is a member of IEEE and IPSJ.

Hiroaki Sakoe received the BE degree from Kyushu Institute of Technology in 1966, and ME and PhD degrees from Kyushu University in 1968 and 1987, respectively. In 1968, he joined NEC Corporation and engaged in speech recognition research. In 1989, he left NEC Corporation to become a professor of Kyushu University. He is now a professor emeritus of Kyushu University.

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Cai, W., Uchida, S. & Sakoe, H. Comparative performance analysis of stroke correspondence search methods for stroke-order free online multi-stroke character recognition. Front. Comput. Sci. 8, 773–784 (2014). https://doi.org/10.1007/s11704-014-3207-6

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  • DOI: https://doi.org/10.1007/s11704-014-3207-6

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