检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:李克奇 栾义忠[1] 夏楠 郭政良 LI Keqi;LUAN Yizhong;XIA Nan;GUO Zhengliang(Institute of Marine Science and Technology,Shandonguniversity,Qingdao 266237;Institute of Control Science andEngineering,Shandong University,Jinan 250061)
机构地区:[1]山东大学海洋研究院,青岛266237 [2]山东大学控制科学与工程学院,济南250061
出 处:《现代制造技术与装备》2019年第10期13-17,共5页Modern Manufacturing Technology and Equipment
摘 要:从视频或图像序列中准确有效提取出焊缝位置信息是实现工业机器人自主弧焊的基础和研究关键。根据主动视觉识别技术,利用CCD摄像机和激光视觉传感器搭建硬件系统,进行焊缝图像采集,提出了一种基于图像预处理与后处理相结合的焊缝检测方法,以适应于复杂焊接环境情况下的焊缝识别。对原始采集图像做图像滤波等预处理工作滤除噪声和提高焊缝图像清晰度,通过改进图像分割和孤点滤波滤等图像后处理提取出焊缝感兴趣区域,最后通过几何分析法和斜率法提取出焊缝中心线和特征点,得到准确的焊缝位置特征信息,从而完成图像信息到焊缝位置信息转换。实验仿真结果表明,所提出算法在搭建硬件系统上的焊缝识别率达到92%,能够把误检率控制在11%左右,能够在复杂背景情景下准确提取出焊缝位置信息,满足工程应用要求。Accurate and effective extraction of weld position information from video or image sequences is the basis and key to realize the independent arc welding of industrial robots. According to the active visual recognition technology, the CCD camera and laser vision sensor are used to build the hardware system to weld the weld image. A weld seam detection method based on image pre-processing and post-processing is proposed to adapt to the complex welding environment. Weld seam identification. Perform pre-processing work such as image filtering on the original acquired image to filter out noise and improve the sharpness of the weld image. The image is extracted by image post-processing such as image segmentation and orphan filter filtering to extract the region of interest of the weld, and finally pass the geometric analysis method and slope. The method extracts the weld center line and feature points, and obtains accurate weld position feature information, thereby completing image information to weld position information conversion. The experimental results show that the proposed algorithm can achieve a weld seam recognition rate of 92% on the hardware system, and can control the false detection rate to about 11%. It can accurately extract the weld position information under complex background scenarios to meet engineering application. Claim.
分 类 号:TP242.2[自动化与计算机技术—检测技术与自动化装置]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.112