To reduce interference to the grayscale of an image due to the reflective characteristics of the PCBA components in a smartphone, improve the integrity of the edge connection, and reduce the number of false edges, this paper proposes an improvement in the traditional Canny operator to extract the PCBA from smartphone edge information. First, considering the characteristics of filter denoising and gradient retention, the use of improved guide filters with “dynamic” penalty factors instead of Gaussian filters reduces the loss of edge points. Thereafter, the traditional double threshold method is replaced with the nearest neighbor local adaptive threshold, which is used to solve the problem of inaccurate threshold segmentation due to frequent grayscale changes in the dense area of the component and the small difference between the background and the target. Experimental results show that a sliding window of 19 has the best threshold segmentation effect, and the number of false edges is minimized. The image processed by this method has more complete and refined edges, the number of false edges is greatly reduced, and the dense local-component area and edge details are retained, which meets the edge detection accuracy requirements of pixel-level mobile phone PCBAs.文章编号