摘要
针对电厂高温管道红外图像背景复杂、干扰较多的特点,结合电厂巡检机器人系统对图像处理算法的需求,提出了基于改进二维最大类间方差法(OTSU)和区域生长法的电厂高温管道缺陷定位与分割方法。将红外图像灰度化后,通过改进二维OTSU进行预分割,提取出管道区域;基于管道区域灰度直方图,结合邻域灰度均值,实现多种子点的自动检测与定位;采用基于生长区域灰度均值和标准差的自适应阈值以及基于Prewitt算子的梯度幅值改进的生长准则完成缺陷区域的分割。实验证明,所提算法不仅能实现电厂高温管道多缺陷自动检测与定位,而且能精确地提取出缺陷区域,准确性高且具有良好的实时性。
In this study,we consider the complex background and high interference that adversely affect infrared images of high-temperature pipelines in power plants and the requirements of image processing algorithms for inspection robot systems.We propose a high-temperature pipeline defect detection and extraction method based on an improved two-dimensional Otsu and region growth algorithms.After grayscale conversion,a 2D Otsu method was used to extract the pipeline area.Based on the grayscale histogram of the pipeline region and the average gray value of the neighborhood,automatic detection and positioning of multiple sub-points were realized.The segmentation of the defect area was accomplished using two methods.The adaptive threshold was determined based on the gray mean and standard deviation values of the growth area,while the growth criterion was improved using the gradient amplitude of the Prewitt operator.The experimental results show that the proposed algorithm can not only realize the automatic detection and positioning of various defects in high-temperature pipelines of power plants,but it additionally segments the defect regions more accurately with high accuracy and good real-time performance.
作者
彭道刚
尹磊
戚尔江
胡捷
杨晓伟
PENG Daogang;YIN Lei;QI Erjiang;HU Jie;YANG Xiaowei(College of Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Power plant of Baoshan Iron and Steel Co.,Ltd,Shanghai 201900,China;Shanghai Baosight Software Co.,Ltd,Shanghai 201203,China)
出处
《红外技术》
CSCD
北大核心
2021年第5期502-509,共8页
Infrared Technology
关键词
电厂巡检机器人
红外图像
高温管道缺陷分割
改进二维OTSU
改进区域生长法
power plant inspection robot
infrared image
high temperature pipeline defect detection
improved two-dimensional OTSU
improved region growing algorithm
