摘要
目的环境干扰及光学元件不稳定等因素往往会造成钢板表面图像照度不均,钢板表面的微小缺陷具有图像灰度不均、对比度低、形态微小等特点,给后续图像分析和缺陷识别带来因难。为此,提出一种钢板表面低对比度微小缺陷图像增强和分割算法,以消除照度不均并突出缺陷信息,从而有效分割缺陷目标。方法采用小波—同态滤波算法进行图像增强处理,即先利用小波变换对图像进行分解,再基于同态滤波对小波低频系数进行图像灰度修正,同时对高频系数进行高通滤波,然后将处理后的小波低频系数和高频系数进行重构得到增强的图像,从而达到消除照度不均、增强缺陷细节信息的目的。最后利用最大类间方差法(Otsu法)确定自适应阈值提供给Canny算子进行边缘检测。结果采用本文算法对钢板表面多类型低对比度表面微小缺陷进行研究,有效消除了光照不均;单一的Otsu阈值分割和Canny算子难以有效检测这些缺陷,而本文Otsu-Canny算法的正确检测率达96%。结论采用小波—同态滤波进行图像增强处理后,再利用Otsu-Canny算法对钢板表面多类型、低对比度的微小缺陷进行边缘检测取得了良好效果。
Objective Steel plates are important raw materials in industry.In its manufacturing process,a variety of surface defects inevitably arise.These surface defects have a negative effect on the appearance and performance of the product;thus,detecting and controlling them in time is necessary.At present,an increasing number of iron and steel manufacturing enterprises use the machine vision method to detect and identify steel-plate surface defects automatically.The defect detection of the steel-plate surface based on machine vision collects the image of the steel-plate surface by using a charge-coupled device camera.By image denoising and enhancement,the defect image is segmented,the defect features are extracted,and the defect classification is conducted.In image acquisition,being disturbed by the on-site environment of the production line is unavoidable,as are the reflection of the steel plate,the illumination environment or the instability of the optical elements,often resulting in the non-uniform illumination of the image.If the image is not enhanced,great interference in the detection and recognition of small surface defects of the steel plate would occur.The common characteristics of small defects on the steel plate surface are non-uniform gray scale,low contrast between defects and background,obscure edge,diverse and small shape,and a small proportion of a defective area in the entire image,which is even mixed with noise.The contrast between the surface defect of the steel plate and its background is low.To conduct subsequent image analysis and defect recognition effectively,we need to conduct image enhancement processing to emphasize the surface defect information.The purpose of image enhancement is to make the original image clear or emphasize interesting features,thereby improving the overall contrast of the image and enhancing the local details of the image,which has good visual effect and rich information features.On this basis,the surface defect target is segmented from the background by image segmentation
作者
汤勃
孔建益
王兴东
刘钊
刘怀广
Tang Bo;Kong Jianyi;Wang Xingdong;Liu Zhao;Liu Huaiguang(School of Mechanical and Automation Engineering,Wuhan University of Science and Technology,Wuhan 430081,China;College of Computer Science and Technology,Wuhan University of Science and Technology,Wuhan 430065,China)
出处
《中国图象图形学报》
CSCD
北大核心
2020年第1期81-91,共11页
Journal of Image and Graphics
基金
国家自然科学基金项目(51874217).
关键词
机器视觉
表面缺陷
低对比度
小波变换
同态滤波
machine vision
surface defects
low contrast
wavelet transform(WT)
homomorphic filtering
