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Offline Chinese handwriting recognition: an assessment of current technology |
| Sargur N. Srihari, Xuanshen Yang, Gregory R. Ball |
| Center of Excellence for Document Analysis and Recognition (CEDAR), Department of Computer Science and Engineering, University at Buffalo, State University of New York, Amherst, NY14228, USA |
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Abstract Offline Chinese handwriting recognition (OCHR) is a typically difficult pattern recognition problem. Many authors have presented various approaches to recognizing its different aspects. We present a survey and an assessment of relevant papers appearing in recent publications of relevant conferences and journals, including those appearing in ICDAR, SDIUT, IWFHR, ICPR, PAMI, PR, PRL, SPIEDRR, and IJDAR. The methods are assessed in the sense that we document their technical approaches, strengths, and weaknesses, as well as the data sets on which they were reportedly tested and on which results were generated. We also identify a list of technology gaps with respect to Chinese handwriting recognition and identify technical approaches that show promise in these areas as well as identify the leading researchers for the applicable topics, discussing difficulties associated with any given approach.
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Issue Date: 05 June 2007
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