Using hidden Markov model for Chinese business card recognition

Y. K. Wang, K. C. Fan, Y. T. Juang, T. H. Chen

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


Business card recognition is a difficult problem. Characters in business card are small with diverse font types. In this paper, an approach using left-right hidden Markov model is proposed for business card recognition. The hidden Markov model will output a top-10 candidate list as its recognition result. A postprocessing stage is followed to improve the recognition result. The postprocessing stage uses bigram table as linguistic information to search optimized recognition result from the top-10 candidate list. Our experiments are built on the recognition of company item and address item in Chinese business cards. Bigram table and hidden Markov models are trained with a telephony database. 100 address items and 30 company items are used for testing. Experimental results reveal the validity of our proposed method.

Original languageEnglish
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) 2001 - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001


ConferenceIEEE International Conference on Image Processing (ICIP) 2001


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