基于局部轮廓视觉特征提取的铜金属的杂质检测方法

Copper metal impurity detection method based on local contour visual feature extraction

采用计算机视觉图像处理技术实现铜金属的杂质检测，提高检测精度，提出一种基于局部轮廓视觉特征提取的铜金属的杂质检测方法。对采集的铜金属原材料图像进行局部轮廓视觉特征提取，对图像进行小波阈值滤波，采用Harris角点检测方法进行图像的杂质成分点标记，实现对图像的杂质噪点优化检测。仿真结果表明，采用该方法进行图像处理和铜金属杂质检测，精度较高，图像的平滑性较好。

Proposed a method based on the local contour visual feature extraction of copper metal impurities detection method. The acquisition of copper metal raw material image were local contour visual feature extraction, image wavelet threshold filtering, image of impurity composition marked by Harris corner detection method, impurity noise on image detection optimization. The simulation results show that the method is used for image processing and copper metal impurity detection, with higher accuracy and better image smoothness.