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Markov process in pattern recognition

Cai, Jinhai & Liu, Zhi-Qiang (2001) Markov process in pattern recognition. International Journal of Image and Graphics, 1(2), pp. 287-311.

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Abstract

Using the Markov random process, we developed two new approaches to pattern recognition: (1) Hidden Markov model for modeling spectral features for recognizing 2D shapes. This is because Fourier spectra are suitable for describing 2D shapes of simple closed contours and probabilistic models are capable of coping with random variations in object shapes. We will analyze the properties of spectral features derived from contours of 2D shapes and use these features in 2D pattern recognition. (2) Markov random fields for modeling 2D structural and statistical features. We will give a theoretic analysis of this approach, discuss the issues in the design of neighborhood system and cliques for Markov random field models, and analyze the properties of the models.

We have applied the proposed approach to the recognition of unconstrained handwritten numerals and 2D shapes. Our extensive experimental results show that the proposed approach can achieve a higher performance than that reported recently in the literature.

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154 since deposited on 11 Apr 2006
19 in the past twelve months

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ID Code: 3868
Item Type: Journal Article
Additional Information: j.cai@qut.edu.au
Keywords: Pattern Recognition, Markov Random Field Models, Hidden Markov Models, 2D Shapes, Handwriting Recognition
DOI: 10.1142/S0219467801000189
ISSN: 0219-4678
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2001 World Scientific Publishing
Copyright Statement: Electronic version of an article published as International Journal of Image and Graphics 1(2):pp. 287-311.
Deposited On: 11 Apr 2006
Last Modified: 31 May 2012 12:33

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