吉林大学学报（信息科学版）2023，Vol.41Issue(6)：1072-1078,7.
基于CycleGAN图像增强的输送皮带洒料检测技术
Spray Detection Technology for Conveyor Belt Based on CycleGAN Image Enhancement
摘要
Abstract
In order to solve the problem of unstable lighting conditions,dust and other interference factors when the camera monitors the distribution of mineral materials on the conveyor belt of the coal mine,the effect of directly applying binarization to the camera image to obtain the distribution of mineral materials is unstable and prone to missed inspections,a conveyor belt spill detection technology based on Cycle GAN(Cycle Generative Adversarial Networks)image enhancement is proposed.First,the image of the coal mine conveyor belt collected by the camera is used as input,and the image is enhanced through Cycle GAN;after that,the binary method is used to segment the image to accurately obtain the target area of the conveyor belt;finally,the threshold method and morphological processing are used to analyze the conveyor belt.The belt spraying area is judged and detected.The experimental results show that this technology can effectively monitor the spillage on the conveyor belt,and can improve the monitoring accuracy on the basis of traditional monitoring methods.关键词
循环生成对抗网络/图像增强/输送皮带/检测Key words
cycle generative adversarial networks(Cycle GAN)/image enhancement/conveyor belt/detection分类
信息技术与安全科学引用本文复制引用
吴淑娟,张铭..基于CycleGAN图像增强的输送皮带洒料检测技术[J].吉林大学学报（信息科学版）,2023,41(6):1072-1078,7.基金项目
福建省自然科学基金资助项目(2022J05245) （2022J05245）
