机器视觉在单板缺陷检测中的应用

单板是胶合板制造的主要原料。为了实现单板表面缺陷检测技术的智能化，降低人力成本，提高检测合格率，现已将机器视觉技术应用于缺陷检测中。在机器视觉系统中，图像处理和分析算法尤为重要。如何提高算法的准确性和鲁棒性一直是研究的重点。文中基于对大量文献和实验结果的分析，介绍机器视觉的应用现状，并对单板表面缺陷检测过程中的图像去噪、图像分割、特征提取等方法进行总结，概括相关方法的原理、特点、局限性以及适用范围，并对未来技术发展趋势进行展望。

Application of Machine Vision to Veneer Defect Detection

Veneer is the main raw material for plywood manufacturing. In order to realize the intelligent veneer surface defect detection technology, reduce labor cost and improve the detection qualified rate, machine vision technology has been applied to the defect detection. In machine vision system, image processing and analysis algorithm is particularly important, and how to improve the accuracy and robustness of algorithm remains the focus of research. Based on the analysis of literature and experimental results, this paper describes the current application of machine vision, summarizes the methods of image denoising, image segmentation and feature extraction in the process of veneer surface defect detection, and concludes the principle, characteristics, limitations and scope of application of these methods. The prospects of the future trend of technology development are also discussed.