Research on prevention of blocking bunker by image segmentation based on variational level set
LI Dan
XIAO Li-qing
SUN Jin-ping
TIAN Xiu-ling
CHENG De-qiang
Abstract：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.
Keywords：image segmentationblock bunker accidentvariational level setgeodesic active contour modelChan and Vese model
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)