基于改进背景减法的焊缝缺陷检测图像分割

Zhichao Liao, Jun Sun
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引用次数: 9

摘要

背景减法是计算机视觉中检测运动目标的一种重要方法。背景重构算法是基于背景像素强度在图像序列中以最大概率出现的假设。本文提出了一种基于背景像素强度在图像序列中以最大概率出现且背景像素分布符合高斯分布的改进背景减法的焊缝缺陷实时检测算法。该算法已成功应用于焊缝缺陷在线检测中。该方法可以很好地提取焊缝缺陷,并对焊缝缺陷进行粗略分类。实验结果表明,该算法能够满足焊缝缺陷在线连续检测的效率要求,实现焊缝缺陷的自动、成功检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image segmentation in weld defect detection based on modified background subtraction
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. This 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. Experimental 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.
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