基于 CycleGAN 图像增强的输送皮带洒料检测技术

吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (6): 1072-1078.

基于 CycleGAN 图像增强的输送皮带洒料检测技术

吴淑娟¹ , 张铭²

1. 闽西职业技术学院智能制造学院, 福建龙岩 364021; 2. 龙岩学院物理与机电工程学院, 福建龙岩 364012

收稿日期:2023-05-25 出版日期:2023-11-30 发布日期:2023-12-01
作者简介:吴淑娟(1975— ), 女, 福建龙岩人, 闽西职业技术学院副教授, 主要从事自动化技术研究, ( Tel) 86-13950809890 (E-mail)778175315@ qq. com
基金资助:
福建省自然科学基金资助项目(2022J05245)

Spray Detection Technology for Conveyor Belt Based on CycleGAN Image Enhancement

WU Shujuan ¹, ZHANG Ming²

1. School of Intelligent Manufacturing, Minxi Vocational and Technical College, Longyan 364021, China; 2. College of Physics and Mechanical and Electrical Engineering, Longyan College, Longyan 364012, China

Received:2023-05-25 Online:2023-11-30 Published:2023-12-01

摘要/Abstract

摘要： 为解决摄像头监拍煤矿输送皮带上矿料分布情况时, 存在的光照条件不稳定、扬尘等干扰因素, 从而导致直接对摄像头画面应用二值化获得矿料分布效果不稳定, 容易出现漏检的问题, 提出了一种基于 Cycle GAN(Cycle Generative Adversarial Networks)图像增强的输送皮带洒料检测技术。首先利用摄像头采集的煤矿输送皮带图像作为输入, 经过 Cycle GAN 进行图像增强; 然后采取二值化方法进行图像分割, 准确获取输送皮带洒料的目标区域; 最后采用阈值法和形态学处理对输送皮带洒料区域进行判断和检测。实验结果表明, 该技术能有效地监测输送皮带上的洒料情况, 并且在传统监测方法的基础上可提高监测准确率。

关键词: 循环生成对抗网络, 图像增强, 输送皮带, 检测

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.

Key words: cycle generative adversarial networks(Cycle GAN), image enhancement, conveyor belt, detection

中图分类号:

TP391. 7

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.

WU Shujuan , ZHANG Ming. Spray Detection Technology for Conveyor Belt Based on CycleGAN Image Enhancement [J]. Journal of Jilin University (Information Science Edition), 2023, 41(6): 1072-1078.