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机器视觉在木材缺陷检测领域应用研究进展
引用本文:范佳楠,刘英,杨雨图,缑斌丽.机器视觉在木材缺陷检测领域应用研究进展[J].世界林业研究,2020,33(3):32-37.
作者姓名:范佳楠  刘英  杨雨图  缑斌丽
作者单位:南京林业大学机械电子工程学院,南京210037;南京林业大学机械电子工程学院,南京210037;南京林业大学机械电子工程学院,南京210037;南京林业大学机械电子工程学院,南京210037
基金项目:江苏省重点研发计划(产业前瞻与关键核心技术)项目(BE2019112);江苏省政策引导类计划(国际科技合作)项目(BZ2016028)。
摘    要:为了提高木材利用率,采用机器视觉来实现木材缺陷快速而稳定的检测,不仅可以克服人工检测效率低、劳动强度大、准确率低等弊端,而且对提高木材加工企业的智能化水平具有重要意义。文中概述了机器视觉检测技术及设备的国内外研究现状,介绍基于机器视觉检测木材缺陷所涉及的相关理论和算法研究,以及相关图像处理算法的优缺点;针对机器视觉应用在木材缺陷检测领域存在的不足,提出机器视觉木材表面检测应进一步向人工智能方向发展,以提高木材缺陷检测效率及准确性。

关 键 词:机器视觉  木材缺陷  检测算法
收稿时间:2019/8/7 0:00:00
修稿时间:2020/2/28 0:00:00

Research Progress in the Application of Machine Vision to Wood Defect Detection
Fan Jianan,Liu Ying,Yang Yutu and Gou Binli.Research Progress in the Application of Machine Vision to Wood Defect Detection[J].World Forestry Research,2020,33(3):32-37.
Authors:Fan Jianan  Liu Ying  Yang Yutu and Gou Binli
Institution:College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
Abstract:China has limited timber resources. In order to improve the utilization of wood, machine vision is used to achieve rapid and stable detection of wood defects, which can not only overcome the shortcomings of low efficiency, high labor intensity and low accuracy, but also play an important role in improving the intelligence level of wood processing enterprises. This paper summarizes the research on machine vision based detection technology and relevant equipment at home and abroad, and introduces the related theories and algorithms involved in machine vision detection of wood defects as well as the advantages and disadvantages of related image processing algorithms. In view of the shortcomings of the application of machine vision in the field of wood defect detection, it is proposed that machine vision based wood surface detection should be further developed in the direction of artificial intelligence, in order to improve the efficiency and accuracy of wood defect detection.
Keywords:
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