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Recognition of the type of welding joint based on line structured-light vision

机译:基于线结构光视觉的焊接接头类型识别

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To recognize the type of welding joint is an essential precondition for extracting features of weld seam and guiding robot tracking seam automatically. A method based on a line laser structured-light vision for recognizing the type of welding joint is studied in this paper. Images of welding joint captured by camera are preprocessed firstly for noise reduction and enhancement with wavelet transform, and the reconstructed images are converted to binary ones using appropriate thresholds. Then some features of binary images are further extracted and formed feature vectors which are input into a PNN classifier for classification. Combined with the position relationship of laser and camera, four types of welding joint are eventually recognized. Experimental results show that, this method has a high recognition rate.
机译:识别焊接接头的类型是提取焊缝特征并自动引导机器人跟踪焊缝的必要前提。本文研究了一种基于线激光结构光视觉的焊接接头类型识别方法。首先对相机捕获的焊接接头图像进行预处理,以通过小波变换进行降噪和增强,然后使用适当的阈值将重建的图像转换为二进制图像。然后,进一步提取二进制图像的某些特征,并形成特征向量,将其输入到PNN分类器中进行分类。结合激光和摄像机的位置关系,最终识别出四种焊接接头。实验结果表明,该方法具有较高的识别率。

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