A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information

FAN Jiulun; ZHANG Hong

doi:10.1049/cje.2015.07.031

Volume 24 Issue 3

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FAN Jiulun and ZHANG Hong, “A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information,” Chinese Journal of Electronics, vol. 24, no. 3, pp. 622-626, 2015, doi: 10.1049/cje.2015.07.031

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FAN Jiulun and ZHANG Hong, “A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information,” Chinese Journal of Electronics, vol. 24, no. 3, pp. 622-626, 2015, doi: 10.1049/cje.2015.07.031

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A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information

doi: 10.1049/cje.2015.07.031

FAN Jiulun^1,2,
ZHANG Hong^{1,2
,}

1.
School of Electronic Engineering, Xidian University, Xi'an 710071, China;
2.
School of Telecommunication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

Funds: This work is supported by the National Science Foundation of China (No.61102095, No.61340040), and the Provincial Natural Science Foundation research project of Shanxi (No.2012JQ8045).

More Information

Corresponding author: ZHANG Hong (corresponding author) was born in Pingyao, Shanxi province in 1976. She received M.S. degree from Xi'an University of Science and Technology in 2002, and then worked at Xi'an University of Posts and Telecommunications. Currently, she is a Ph.D. candidate at the school of Electronic Engineering of Xidian University. Her research interests focus on pattern recognition and image processing. (Email: zhmlsa@xupt.edu.cn)
Received Date: 2013-10-25
Rev Recd Date: 2014-05-12
Publish Date: 2015-07-10

Abstract

Abstract

Thresholding based on gray-gray cooccurrence matrix is a local thresholding technique. Relative entropy is usually used to gauge the relative difference of uncertainties in two physical systems, and the relative entropy-based asymmetrical co-occurrence matrix thresholding has been applied successfully. We propose to construct symmetrical co-occurrence matrix with the statistical spatial information from the mean values in object and background regions of an image. In this way, a unique relative entropy-based symmetrical co-occurrence matrix thresholding method is derived. Computer-simulation results demonstrated the higher adaptability and efficiency of the proposed method, as compared with square distance based symmetrical co-ocurrence matrix thresholding, Otsu's and relative entropy methods.
- Image segmentation,
- Symmetrical cooccurrence matrix,
- Relative entropy thresholding,
- Region mean value

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References(27)

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