基于机器视觉的PCB板表面缺陷检测方法研究进展

Research progress of the PCB surface defect detection method based on machine vision

基于机器视觉的缺陷检测方法可有效提高生产效率和降低质检成本,在现代化工业生产中得到了广泛应用。对基于机器视觉的PCB板表面缺陷检测方法涉及的图像采集系统、图像预处理技术进行综述;对基于图像分割、特征提取、机器学习和混合技术的检测算法进行分析,总结了各种算法的主要思想、适用范围以及局限性;同时对未来的发展方向进行了展望,为该领域的研究人员提供参考。机器视觉作为现代工业生产中一项不可或缺的关键技术,在PCB板缺陷检测领域仍有较大的发展空间,尤其是进一步智能化,仍有待深入研究。

Defect detection methods based on machine vision can effectively improve production efficiency and reduce the costs of quality inspection, so they have been widely applied in modern industrial production. This article introduces the image acquisition system and image preprocessing technology involved in the PCB surface defect detection method based on machine vision, analyzes detection algorithms based on image segmentation, feature extraction, machine learning and hybrid technology, summarizes the main ideas, application scopes and limitations of all kinds of algorithms, prospects the future direction, which can offer a reference for researchers in this field. Machine vision, as an essential key technology in modern industrial production, still has much room for development in the field of PCB defect detection. In particular, further intelligence needs to be studied in depth.