ABSTRACT
Image-based separation of coal and gangue is susceptible to the external environment. This paper studies the effects of illuminance and external moisture on grayscale and texture features of coal and gangue images. We first build an image acquisition system and construct an image dataset of coals and gangues under different illuminance and external moisture. Secondly, we extract four grayscale parameters including gray value corresponding to the maximum frequency, gray average, variance, and skewness and four texture parameters including entropy, contrast, energy, and correlation of these images. Thirdly, we compare these parameters by normalizing the values of coal and gangue. The result shows that illuminance has a greater influence on the grayscale parameters than the texture parameters, and the grayscale maximum fluctuation value is 0.21 while the value of texture is 0.16. External moisture has a greater influence on the texture parameters than the grayscale parameters, and the grayscale maximum fluctuation value is 0.22 while the value of texture is 0.29. The study of the influence of illuminance and external moisture on the features of coal and gangue images could provide an essential guide for image-based identification of coal and gangue under working conditions.
Acknowledgments
The authors would like to acknowledge the Projects funded by the National Natural Science Foundation of China (Grant No. 51834006), the Projects of Shaanxi Provincial Science and Technology Department (Grant No. 2018GY-039).