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吴鑫1,李强1,焦京海2,齐铂金3. 一种基于先验知识的弧焊机器人图像处理方法[J]. 焊接学报, 2018, 39(1): 123-128. DOI: 10.12073/j.hjxb.2018390028
引用本文: 吴鑫1,李强1,焦京海2,齐铂金3. 一种基于先验知识的弧焊机器人图像处理方法[J]. 焊接学报, 2018, 39(1): 123-128. DOI: 10.12073/j.hjxb.2018390028
Wu Xin1, Li Qiang1, Jiao Jinghai2, Qi Bojin3. An image processing method of welding robot based on prior knowledge[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(1): 123-128. DOI: 10.12073/j.hjxb.2018390028
Citation: Wu Xin1, Li Qiang1, Jiao Jinghai2, Qi Bojin3. An image processing method of welding robot based on prior knowledge[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(1): 123-128. DOI: 10.12073/j.hjxb.2018390028

一种基于先验知识的弧焊机器人图像处理方法

An image processing method of welding robot based on prior knowledge

  • 摘要: 在弧焊机器人视觉检测的CCD直接拍摄图像方法中,针对带有黑笔记号、划痕、并与焊缝交叉干扰的复杂对接焊缝图像,文中提出了一种实用的焊缝轨迹的识别方法,并对该算法中的骨架细化及边缘链的拆分、合并剪枝和基于先验知识的位置关系判断等关键问题进行重点阐述. 结果表明,该算法能有效地去除复杂焊缝图像中的黑笔记号、划痕和交叉干扰,最终自动提取焊缝轨迹. 该算法具有较强的适应性和可扩展性,稍加改进就可应用于其它复杂图像上. 如带电弧光或结构光等的图像. 该算法能为弧焊机器人视觉检测的智能化的进一步提高提供一定的技术参考.

     

    Abstract: In the vision detection methods for shooting the image directly with CCD of arc welding robot, This paper proposes a practical recognition algorithm for complex weld images with black note marks, scratches, and cross interferences with welds, and puts the emphasis on several key issues of this algorithm, such as the skeleton thinning, splitting, merging and pruning of edge chains, and the judgments of location relations based on prior knowledge, etc. The experimental results demonstrate that the algorithm can effectively remove the black notes, scratches and cross interferences and can automatically extract the weld track in complex weld images. The algorithm has strong adaptability and expandability, and can be applied to other complex images with a slight improvement,such as images with arc light or structured light, etc. The algorithm can provide some technical reference for further improving the intelligent vision detection of arc welding robot.

     

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