基于直方图差异的工业产品表面缺陷检测方法

Surface Defect Detection Method of Industrial Products Based on Histogram Difference

随着计算机视觉的高速发展,在产品检测方面,人工劳动力逐渐被机器视觉取代,特别是在工作人员不宜长期逗留的生产环境中,工业产品的表面缺陷自动检测是现代化工业的必然趋势。文中将缺陷检测看作一种特定的图像分割问题,将产品表面看作背景、以表面缺陷为前景来进行提取。在所提方法中,分割的主要依据是前景和背景的灰度分布直方图差异程度以及背景分布和先验背景分布的直方图相似程度;结合非参数统计活动轮廓模型和先验分布,以产品表面的灰度分布为背景的先验信息,构造对应的能量函数,然后最小化能量函数得到相应的水平集函数迭代方程,以更高效地进行缺陷检测。相关实验表明,所提出的缺陷检测方法在视觉上有较大提升,在检测正确率、虚警率和漏检率等数值指标上也有较大提升。

With the rapid development of computer vision,human labor is gradually replaced by machine vision in product detection,especially in the production environment that workers should not stay long.Automatic detection of surface defects of industrial products is an inevitable trend of modern industry.In this paper,defect detection is regarded as a special image segmentation problem,and it is extracted by taking product surface as the background and surface defects as the foreground.In this paper,the segmentation is based on the difference between the gray distribution histogram of the foreground and the background,and the similarity between the background and prior background distribution histogram.Combining nonparametric statistical activity contour model and prior distribution,the gray distribution of the product surface is considered as the background prior information to construct the corresponding energy function,then the corresponding iteration equation of level set function is obtained by minimizing the energy function,so the defect detection can be more efficient.Experiments show that the proposed defect detection method is improved significantly in vision and numerical indexes such as detection accuracy,false alarm and missing detection.