Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition

Hee Seon Park; Seong Whan Lee

doi:10.1109/ICDAR.1995.599024

Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition

Hee Seon Park, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

In recent years, there have been some attempts to extend one-dimensional hidden Markov model (HMM) to two-dimensions. This paper presents a new statistical model for image modeling and recognition under the assumption that images can be represented by a third-order hidden Markov mesh random field (HMMRF) model. We focus on two major problems: image decoding and parameter estimation. A solution to these problems is derived from the scheme based on a maximum, marginal a posteriori probability criterion for the third-order HMMRF model. We also attempt to illustrate how theoretical results of HMMRF models can be applied to the problems of handwritten character recognition.

Original language	English
Title of host publication	Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995
Publisher	IEEE Computer Society
Pages	409-412
Number of pages	4
ISBN (Electronic)	0818671289
DOIs	https://doi.org/10.1109/ICDAR.1995.599024
Publication status	Published - 1995
Event	3rd International Conference on Document Analysis and Recognition, ICDAR 1995 - Montreal, Canada Duration: 1995 Aug 14 → 1995 Aug 16

Publication series

Name	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume	1
ISSN (Print)	1520-5363

Conference

Conference	3rd International Conference on Document Analysis and Recognition, ICDAR 1995
Country/Territory	Canada
City	Montreal
Period	95/8/14 → 95/8/16

Bibliographical note

Funding Information:
The authors wish to thank Pierre A. Devijver for his helpful comments and encouragement. This work was supported by the Directed Basic Research Fund of Korea Science and Engineering Foundation.

Publisher Copyright:
© 1995 IEEE.

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICDAR.1995.599024

Cite this

Park, H. S., & Lee, S. W. (1995). Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995 (pp. 409-412). Article 599024 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICDAR.1995.599024

Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition. / Park, Hee Seon; Lee, Seong Whan.
Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995. IEEE Computer Society, 1995. p. 409-412 599024 (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, HS & Lee, SW 1995, Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition. in Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995., 599024, Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, vol. 1, IEEE Computer Society, pp. 409-412, 3rd International Conference on Document Analysis and Recognition, ICDAR 1995, Montreal, Canada, 95/8/14. https://doi.org/10.1109/ICDAR.1995.599024

Park HS, Lee SW. Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition. In Proceedings of the 3rd International Conference on Document Analysis and Recognition, ICDAR 1995. IEEE Computer Society. 1995. p. 409-412. 599024. (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). doi: 10.1109/ICDAR.1995.599024

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abstract = "In recent years, there have been some attempts to extend one-dimensional hidden Markov model (HMM) to two-dimensions. This paper presents a new statistical model for image modeling and recognition under the assumption that images can be represented by a third-order hidden Markov mesh random field (HMMRF) model. We focus on two major problems: image decoding and parameter estimation. A solution to these problems is derived from the scheme based on a maximum, marginal a posteriori probability criterion for the third-order HMMRF model. We also attempt to illustrate how theoretical results of HMMRF models can be applied to the problems of handwritten character recognition.",

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AB - In recent years, there have been some attempts to extend one-dimensional hidden Markov model (HMM) to two-dimensions. This paper presents a new statistical model for image modeling and recognition under the assumption that images can be represented by a third-order hidden Markov mesh random field (HMMRF) model. We focus on two major problems: image decoding and parameter estimation. A solution to these problems is derived from the scheme based on a maximum, marginal a posteriori probability criterion for the third-order HMMRF model. We also attempt to illustrate how theoretical results of HMMRF models can be applied to the problems of handwritten character recognition.

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Hidden markov mesh random fiehd: Theory and its application to handwritten character recognition

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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