Snake模型和遗传算法在特殊焊缝提取中的应用

Application of Snake model and genetic algorithm in special weld seam extraction

针对CCD直接拍摄图像的弧焊机器人焊缝视觉检测问题,文中提出了一种精确提取带有较大的间断、尖锐的拐点、较多的干扰等特殊焊缝轨迹的算法.该算法先用小波变换进行焊缝边缘线的平滑,得到与最终焊缝距离很近的初始焊缝轨迹,再用基于Snake模型和遗传算法的进行特殊焊缝的精确匹配和提取.结果表明,该算法能进一步提高特殊焊缝轨迹识别的识别和检测精度,具有较强的适应性,也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.

Aimed at the weld vision detection problem of arc welding robot in CCD directly photographed image,an algorithm for the extraction of special weld seam track with large discontinuity,sharp turning point and more interference was proposed.The algorithm firstly use wavelet transform to smooth the weld edge line to get the initial weld track that is very close to the final weld,and then use Snake model and genetic algorithm to get accurate matching and extraction of special welds.Experimental results demonstrate that the algorithm can improve the precision of special weld track recognition and detection,and has strong adaptability,and can also provide some technical reference for further improving the intelligent vision detection of arc welding robot.