基于背景差分法在焊缝缺陷检测中的应用

Weld Defect Inspection Based on Background Subtraction of Gaussian Model

现代工业对于焊接技术的使用越来越多,如何保证焊件质量是焊缝技术的重要环节。在机器视觉中,背景差分法是一种重要的运动检测方法。基于背景像素点在图像序列中被观测到的概率是最大的前提假设,并结合背景像素点可以看作高斯分布的加权的前提假设,提出了一种实时焊缝检测算法。该算法在准确检测焊缝缺陷的同时,能够在一定程度上对焊缝缺陷类别进行分类;既能提高产品的合格率,有通过反馈焊缝缺陷的分类,对焊缝生产线的调节提供帮助。实验结果证实了所提算法的有效性和实时性。

In computer vision, the background subtraction is an important method to detect moving objects. The background reconstruction algorithm is based on the hypotheses that the background pixels intensity appears in image sequence with maximum probability. The paper proposes a real-time weld defect detection algorithm using a modified background subtraction method based on the assumption that the background pixel intensity appears in image sequence with maximum probability and the distribution of the pixels of background conforms to the Gaussian distribution. The algorithm has been successfully applied to the on- line weld defect detection. Our approach can perfectly extract and roughly classify the weld defects. Ex- perimental results show that the proposed algorithm can meet the requirement of the efficiency of on-line continuous detection of weld defects and detect weld defects automatically and successfully.