An HMMRF-based statistical approach for off-line handwritten character recognition

Hee Seon Park, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

We propose a new methodology for off-line handwritten character recognition using a 2D hidden Markov mesh random field (HMMRF)-based statistical approach. In the HMMRF model for character recognition, the inputs to the model are assumed to be sequences of discrete symbols chosen from a finite alphabet. In the proposed methodology, the grey-level input image is first divided into nonoverlapping blocks with same size. Then, each block is encoded into a discrete symbol based on the local features of the block by using the vector quantizer. The HMMRF-based statistical approach necessitates two phases: the decoding phase and the training phase. In both phases we use the lookahead scheme based on a maximum, marginal a posteriori probability criterion for a third-order HMMRF model. In order to verify the performance of the proposed methodology for off-line handwritten character recognition, a large-set handwritten Hangul database was used. Experimental results revealed the viability of the HMMRF-based statistical approach on the task of off-line handwritten character recognition.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages320-324
Number of pages5
Volume2
ISBN (Print)081867282X, 9780818672828
DOIs
Publication statusPublished - 1996 Jan 1
Event13th International Conference on Pattern Recognition, ICPR 1996 - Vienna, Austria
Duration: 1996 Aug 251996 Aug 29

Other

Other13th International Conference on Pattern Recognition, ICPR 1996
CountryAustria
CityVienna
Period96/8/2596/8/29

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Park, H. S., & Lee, S. W. (1996). An HMMRF-based statistical approach for off-line handwritten character recognition. In Proceedings - International Conference on Pattern Recognition (Vol. 2, pp. 320-324). [546841] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.1996.546841