FAN Jiulun, ZHANG Hong. A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information[J]. Chinese Journal of Electronics, 2015, 24(3): 622-626. doi: 10.1049/cje.2015.07.031
Citation: FAN Jiulun, ZHANG Hong. A Unique Relative Entropy-Based Symmetrical Co-occurrence Matrix Thresholding with Statistical Spatial Information[J]. Chinese Journal of Electronics, 2015, 24(3): 622-626. doi: 10.1049/cje.2015.07.031

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

doi: 10.1049/cje.2015.07.031
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).
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  • 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
  • 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.
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