Research on prevention of blocking bunker by image segmentation based on variational level set

被引：0
|
作者：
Li D. [1 ,2 ]
Xiao L.-Q. [1 ,2 ]
Sun J.-P. [1 ,2 ]
Tian X.-L. [1 ,2 ]
Cheng D.-Q. [3 ]
机构：
[1] Xuzhou Institute of Technology, Xuzhou
[2] Machine Viston Applications Engineering and Technology Research Center of Xuzhou, Xuzhou
[3] College of Information and Electric Engineering, China University of Mining and Technology, Xuzhou
来源：
Xiao, Li-Qing (lidanonline@163.com) | 1600年 / China Coal Society卷 / 41期
关键词：
Block bunker accident; Chan and Vese model; Geodesic active contour model; Image segmentation; Variational level set;
D O I：
10.13225/j.cnki.jccs.2015.1175
中图分类号：
学科分类号：
摘要：
Due to the special environment of high noise, low resolution and uneven illumination in coal mine, a coal image segmentation model was established to achieve an accurate detection of large coal, and prevent the occurrence of blocking bunker accident. The new model based on variational level set algorithm improved the GAC and C-V model to segment the coal image. The algorithm fused contour and region model, and the optimal solution of the energy model was solved by solving the steady state solution of partial differential equation and the numerical calculation used the method of the discrete slightest difference. The new method effectively improved the accuracy of calculation, topology adaptive capacity, anti-noise ability and reduced the light sensitivity. Experiment showed that the new model had good robustness in the complex environment of underground coal mine and higher real-time performance, reduced the burden of large coal screening and greatly improved the screening accuracy. © 2016, Editorial Office of Journal of China Coal Society. All right reserved.
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收藏
页码：273 / 278
页数：5
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