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作 者:于向茹 丁健配 李金屏[1,2,3] YU Xiangru;DING Jianpei;LI Jinping(School of Information Science and Engineering,University of Jinan,Jinan 250022,China;Shandong Provincial Key Laboratory of Network Based Intelligent Computing,Jinan 250022,China;Shandong College and University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year,Jinan 250022,China;Shandong Shen Tu Intelligent Science & Technology Co. Ltd.,Jinan 250022,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,山东济南250022 [3]山东省"十三五"高校智能信息处理与感知重点实验室,山东济南250022 [4]山东深图智能科技有限公司,山东济南250022
出 处:《中国科学技术大学学报》2019年第1期49-54,共6页JUSTC
基 金:国家自然科学基金(61701192);山东省重点研发计划(2017CXGC0810);山东省科技重大专项(新兴产业)项目(2015ZDXX0801A03);山东省教育科学规划"教育招生考试科学研究专设课题"(ZK1337212B008)资助
摘 要:针对胎侧和胎肩的杂质缺陷检测,提出了一种基于形态学和投影直方图的方法.首先,图像预处理分割胎侧与胎肩,降低花纹等因素对杂质检测的影响;其次,用局部大津法对图像进行二值化处理,以形态学操作从背景中提取杂质;然后,纵向滤波去掉毛刺;最后,根据水平及垂直方向投影确定杂质的位置.由于杂质的位置是随机的,而且投影曲线符合方波模型,因此根据上述特点筛选检测结果.实验结果表明,该方法能够有效地检测花纹外面的杂质,而且能够满足系统对实时性的要求.A method based on morphology and projection histogram is proposed,which aims at detecting impurities in the sidewall and shoulder of the tire. Firstly,image preprocessing is used to segment the sidewall and shoulder,decreasing the negative influence caused by the tread pattern. Secondly,the binarized images are obtained by using OTSU in the local area,while impurities are extracted from the background by morphological operation. Then,vertical filtering is performed to remove burrs. Finally,the impurity is located by vertical and horizontal projections. The position of the impurity is random,and the projection curves of impurities are consistent with the square wave model,so the impurities are filtered according to the above characteristics of impurity. The experiments show that the proposed method can effectively detect impurities in the sidewall and shoulder outside the tread pattern,and that it can also meet the system requirement of real-time performance.
关 键 词:轮胎杂质 缺陷检测 投影直方图 形态学 方波 纵向滤波
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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