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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 1571795, 18 pages
Research Article

Cloud Model-Based Method for Infrared Image Thresholding

1School of Information Science and Technology, Lingnan Normal University, Zhanjiang 524048, China
2College of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Received 20 January 2016; Accepted 14 April 2016

Academic Editor: Moulay Akhloufi

Copyright © 2016 Tao Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Traditional statistical thresholding methods, directly constructing the optimal threshold criterion using the class variance, have certain versatility but lack the specificity of practical application in some cases. To select the optimal threshold for infrared image thresholding, a simple and efficient method based on cloud model is proposed. The method firstly generates the cloud models corresponding to image background and object, respectively, and defines a novel threshold dependence criterion related with the hyper-entropy of these cloud models and then determines the optimal grayscale threshold by the minimization of this criterion. It is indicated by the experiments that, compared with selected methods, using both image thresholding and target detection, the proposed method is suitable for infrared image thresholding since it performs good results and is reasonable and effective.