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作 者:郝晋一 李鹏程 黄艺美[1,2,3] 李金屏[1,2,3] HAO Jinyi;LI Pengcheng;HUANG Yimei;LI Jinping(School of Information Science and Engineering,University of Jinan,Jinan 250022,Shandong,China;Shandong Provincial Key Laboratory of Network Based Intelligent Computing(University of Jinan),Jinan 250022,Shandong,China;Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-Year(University of Jinan),Jinan 250022,Shandong,China)
机构地区:[1]济南大学信息科学与工程学院,山东济南250022 [2]山东省网络环境智能计算技术重点实验室(济南大学),山东济南250022 [3]山东省“十三五”高校信息处理与认知计算重点实验室(济南大学),山东济南250022
出 处:《山东大学学报(工学版)》2022年第3期9-17,共9页Journal of Shandong University(Engineering Science)
基 金:山东省重点研发计划资助项目(2017CXGC0810);山东省高等学校科技发展计划资助项目(J18KA346和J18KA371)。
摘 要:针对X光机成像问题导致的轮胎顶部拉伸畸变图像,设计一种基于穿线预定位以及众数平滑提取特征的改进穿线法。分割胎侧区域,通过极值滤波消除水平帘线,利用垂直投影确定胎侧区域的粗边界;在胎侧区域进行预穿线确定最终穿线位置,并在选定位置利用众数平滑的方法提取线宽、线距等特征;根据提取的特征值计算线宽比、线距比以及均值、方差设计阈值进行畸变判断。在包含1000张正常图像与600张畸变图像的测试样本中进行试验,漏报率为2.3%,误报率为0%,相对于模板匹配等方法,检测结果更加准确检测、检测速率更快。An improved threading method based on threading pre-targeting and mode smoothing feature extraction was designed to solve the tensile distortion image of tire top caused by X-ray machine imaging problem.The algorithm was as follows:the sidewall region was segmented,the horizontal cord was eliminated by extreme value filtering,and the coarse boundary of sidewall region was determined by vertical projection;the final threading position was determined by pre-threaded in the sidewall area,and the line width and line distance were extracted by mode smoothing method at the selected position;the line width ratio,line spacing ratio and mean variance were calculated according to the extracted eigenvalues,and the design threshold was used to judge the distortion.The test was carried out in the test samples containing 1000 normal images and 600 distorted images.The false positive rate was 2.3%and the false positive rate was 0%.Compared with template matching and other methods,the test results were more accurate and the detection rate was faster.
关 键 词:子午线轮胎 穿线法 图像畸变 顶部拉升 图像分割
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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