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杨倩, 王广伟, 华学明, 吴毅雄. 基于小波变换的熔滴过渡图像的边缘检测[J]. 焊接学报, 2007, (4): 38-40.
引用本文: 杨倩, 王广伟, 华学明, 吴毅雄. 基于小波变换的熔滴过渡图像的边缘检测[J]. 焊接学报, 2007, (4): 38-40.
YANG Qian, WANG Guangwei, HUA Xueming, WU Yixiong. Edge detection of metal transfer image based on wavelet transform[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (4): 38-40.
Citation: YANG Qian, WANG Guangwei, HUA Xueming, WU Yixiong. Edge detection of metal transfer image based on wavelet transform[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (4): 38-40.

基于小波变换的熔滴过渡图像的边缘检测

Edge detection of metal transfer image based on wavelet transform

  • 摘要: 利用小波变换和改进的Prewitt算子对GMAW短路过程的熔滴过渡图像进行边缘检测。用中值滤波对采集到的图像做平滑预处理后,使用小波变换将图像分解到各个层次并提取各层的近似系数和细节系数,将各层的对角细节系数加强适当的倍数后重构图像,使用改进的Prewitt算法对重构图像进行边缘检测。结果表明,此方法可以有效地提取真实熔滴轮廓和熔池边缘,小波分解的层数和加强倍数的大小是影响图像边缘提取效果的重要因素,层数和倍数应根据拍摄到的图像的实际情况确定。

     

    Abstract: Wavelet transform and improved Prewitt operator were used to detect the edge of the droplet image in GMAW.After preprocessing, wavelet transform was used to perform decomposition to different detailed levels, and enhance diagonal detail coefficients by multiplying it with the proper parameters, then reconstruct image. Improved Prewitt operation was used to detect the edge of reconstructed image.The experiment results demonstrate that the method is effective to detect the real outline of droplet and real edge of weld pool, and the levels of decomposition and the multiples are vital factors, which depends on the real image.

     

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