| 机器视觉技术研究进展及展望 |
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| 作者姓名： | 朱 云 凌志刚 张雨强 |
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| 作者单位： | (湖南大学电气与信息工程学院机器人视觉感知与控制技术国家工程实验室，湖南 长沙 410082) |
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| 基金项目： | 基金项目：国家自然科学基金项目(61432004，61672202，61971183)；电子制造业智能机器人技术湖南省重点实验室项目(IRT2018006) |
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| 摘 要： | 摘 要：机器视觉是建立在计算机视觉理论工程化基础上的一门学科，涉及到光学成像、
视觉信息处理、人工智能以及机电一体化等相关技术。随着我国制造业的转型升级与相关研究
的不断深入，机器视觉技术凭借其精度高、实时性强、自动化与智能化程度高等优点，成为了
提升机器人智能化的重要驱动力之一，并被广泛应用于工业生产、农业以及军事等各个领域。
在广泛查阅相关文献之后，针对近十多年来机器视觉相关技术的发展与应用进行分析与总结，
旨在为研究学者与工程应用人员提供参考。首先，总结了机器视觉技术的发展历程、国内外的
机器视觉发展现状；其次，重点分析了机器视觉系统的核心组成部件、常用视觉处理算法以及
当前主流的机器视觉工业软件；然后，介绍了机器视觉技术在产品瑕疵检测、智能视频监控分
析、自动驾驶与辅助驾驶与医疗影像诊断等 4 个典型领域的应用；最后分析了当前机器视觉技
术所面临的挑战，并对其未来的发展趋势进行了展望，为机器视觉技术的发展和应用推广发挥
积极作用。
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| 关 键 词： | 关键词：机器视觉 成像系统 视觉处理算法 视觉软件 挑战与发展趋势 |
Research progress and prospect of machine vision technology |
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| Authors: | ZHU Yun LING Zhi-gang ZHANG Yu-qiang |
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| Affiliation: | (National Engineering Laboratory for Robot Visual Perception and Control Technology, College of Electrical and Information Engineering,
Hunan University, Changsha Hunan 410082, China) |
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| Abstract: | Abstract: Developed from the engineering of computer vision theory, machine vision involves such
technologies as optical imaging, visual information processing, artificial intelligence, and
mechatronics. With the transformation and upgrading of China’s manufacturing industry and
development of relevant research, the machine vision technology, with the advantages of high
precision, real-time performance, high-level automation and intelligence, has become one of the most
significant driving forces for enhancing the intelligence of robots, thus being widely applied in
modern industrial, agricultural, and military fields. In order to provide some guidance for researchers
and engineers, this paper summarized an abundance of literature on machine vision technology, of
which the research, development, and application in the recent decade were analyzed. Firstly, the
development and current situation of machine vision around the world was introduced. Secondly, explorations were made on the key components of machine vision system including lighting, optical
lenses, and cameras, vision processing algorithms including image preprocessing, image visual
position, and segmentation, and the mainstream industrial software of machine vision. Thirdly, four
typical applications of machine vision technology were presented, including production defect
detection, intelligent visual surveillance, autopilot and assisted driving, and medical imaging
diagnosis. Finally, the current challenges faced by machine vision were analyzed, with the future
trends of machine vision predicted. Thus, this paper will play an active role in the development and
application promotion of machine vision science and technology. |
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| Keywords: | Keywords: machine vision imaging system visual processing algorithms vision softeware challenges and development trends |
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