对烧结机机尾断面图像气孔特征提取的研究  

Research on Extraction of Porosity Feature of Cross Section Image of Sintering Machine Tail

作　　者：张学锋 周志远 汤亚玲 储岳中 ZHANG Xue-feng;ZHOU Zhi-yuan;TANG Ya-ling;CHU Yue-zhong(School of Computer Science and Technology, Anhui University of Technology, Anhui Maanshan243000, China)

机构地区：[1]安徽工业大学计算机科学与技术学院,安徽马鞍山243000

出　　处：《重庆工商大学学报（自然科学版）》2022年第2期8-13,共6页Journal of Chongqing Technology and Business University:Natural Science Edition

基　　金：安徽省教育厅重大课题基金(KJ2017ZD05);安徽高校协同创新项目(GXXT-2019-008).

摘　　要：针对烧结机机尾断面气孔特征提取的研究,提出了一种基于OTSU三次迭代RGB颜色通道的多阈值法;为了保证气孔特征提取的准确性和减少图像细节的丢失,采用OTSU法先分别对机尾断面图像的RGB颜色通道3次迭代进行阈值分量计算,再通过RBG三颜色通道占比比值确定权值,计算出一个全局阈值和两个局部阈值进行三阈值图像分割;利用获取的全局阈值将机尾断面图像的火红层和黑矿层进行分割,之后两个局部阈值分别对嵌入在火红层和黑矿层中的气孔进行分割,最终提取出机尾断面的气孔特征;实验表明,方法相较于常规方法能够提取出更多机尾断面的气孔特征及细节,同时提取出的气孔特征轮廓层次感较好,气孔特征提取的准确性较高。Based on the research on the pore feature extraction of the sintering machine tail section,this paper proposed a multi-threshold method based on OTSU three iterations of RGB color channels.In order to ensure the accuracy of stomatal feature extraction and reduce the loss of image details,this method not only adopted the OTSU method to calculate the threshold components of the RGB color channels of the tail section image for three iterations,but also determined the weights by the ratio of the RBG three color channels.Finally,a global threshold and two local thresholds were calculated to perform three-threshold image segmentation.The author used the obtained global threshold to segment the flaming red layer and the black ore layer of the cross-sectional image of the sintering machine tail,and then used two local thresholds to respectively segment the pores embedded in the flaming red layer and the black ore layer.In the end,the author extracted the stomatal features of the tail section of the sintering machine.Experiment shows that compared with conventional methods,this method can extract more stomatal features and details of the tail section of the sintering machine.At the same time,the extracted stomatal feature contours are better and the accuracy of stomatal feature extraction is high.

关 键 词：机尾断面 气孔特征 OTSU法 图像分割 

分 类 号：TP182.1[自动化与计算机技术—控制理论与控制工程]