基于机器视觉的烟草在线检测技术研究进展
Progress in Research on Tobacco Online Inspection Technology Based on Machine Vision
吴玉生 1李安虎 2万亚明 2孟天晨2
作者信息
- 1. 厦门烟草工业有限责任公司,福建 厦门 361022
- 2. 同济大学机械与能源工程学院,上海 201804
- 折叠
摘要
烟草行业高端产品规模的扩大与消费者对产品质量需求的提高,给烟草在线检测技术带来了巨大挑战.针对烟草生产过程中烟丝异物难以剔除,影响卷烟口感、烟草叶片病情害种类繁多且病情复杂、卷烟外包装瑕疵难以识别等问题,传统人工在线检测方法效率低下,且正确率难以保证,无法适应我国烟草行业的高质量发展.在阐明基于机器视觉的烟草在线检测原理的基础上,围绕视觉检测原理和深度学习模型两个方面系统地阐述烟草在线检测技术的研究现状与最新进展,结合现有典型应用分析不同视觉模型以及深度学习模型检测方法的优越性和局限性,进而探讨基于机器视觉的烟草在线检测技术的发展趋势和前景.
Abstract
The expansion of high-end products in the tobacco industry and the increasing demand for product quality from consumers have created significant challenges for online tobacco testing technology.In response to problems such as the difficult removal of foreign objects from tobacco production affecting cigarette taste,various complex diseases from tobacco leaves,and difficulty in identifying cigarette packaging defects,traditional manual online detection methods are inefficient and it is difficult to ensure accuracy,which cannot adapt to the high-quality development of China's tobacco industry.From the perspective of elucidating the principle of tobacco online detection based on machine vision,this study systematically elaborates on the research status and latest progress of tobacco online detection technology based on two key aspects:the visual detection principle and deep learning models.Combined with current typical applications,this study analyzes the advantages and limitations of different visual models and deep learning detection methods,and further explores the development trend and prospects of tobacco online detection technology based on machine vision.
关键词
机器视觉/图像识别/深度学习/在线检测/瑕疵剔除Key words
machine vision/image recognition/deep learning/online inspection/defect removal引用本文复制引用
基金项目
上海市科技创新行动计划(22550711200)
福建中烟工业有限责任公司技术开发项目(2022350200340315)
出版年
2024
NETL
NSTL
万方数据