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吴鑫, 齐铂金. 弧焊机器人结构光视觉检测的图像处理[J]. 焊接学报, 2010, (7): 67-70.
引用本文: 吴鑫, 齐铂金. 弧焊机器人结构光视觉检测的图像处理[J]. 焊接学报, 2010, (7): 67-70.
WU Xin, QI Bojin. Image processing of structure light vision detection of welding robot[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (7): 67-70.
Citation: WU Xin, QI Bojin. Image processing of structure light vision detection of welding robot[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (7): 67-70.

弧焊机器人结构光视觉检测的图像处理

Image processing of structure light vision detection of welding robot

  • 摘要: 对弧焊机器人结构光视觉检测的图像处理算法进行了一定的研究,针对以往的方法提出了一些改进方案并进行了试验.在图像预处理的滤波中,采用区域分割与多尺度检测相结合的方法,克服了单尺度LOG滤波线条容易断续的缺点,又缩小了图像处理的区域,提高了运算速度.在后处理的轮廓提取中,用遗传算法这种全局优化算法进行模板匹配,通过格雷编码、适应度函数确定、概率选择算子、交叉算子、变异算子等,很好地实现了模板匹配和位置坐标提取.结果表明,这些改进的算法,提高了弧焊机器人结构光检测的精度和适应性.

     

    Abstract: Image processing algorithms of welding robot structure light detection were studied.Compared with the traditional image processing algorithm,some improved methods were proposed and tested,In filter of image preprocessing,a method combing region segmentation with multi-scale detection was adopted,and could overcome the disadvantage of contour easy breaking with single dimension LOG filter and minish the region to be processed,and easy to improve the processing speed.In contour pick-up of post-processing,Genetic Algorithm as a global optimization algorithm,was adopted to realize template matching.By grey coding method,fitness function,selection operators,crossover operators,mutation operators and so on,finally realize template matching and coordination pick-up the experimental results show that these improved methods can improve the precision and adaptability of welding robot structure light detection.

     

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