In light of the intricate texture, subtle imperfections, and diverse issues present in PCB boards, a novel edge detection method tailored for the internal circuits of PCB boards is proposed. Initially, adaptive local noise reduction filtering is utilized to preprocess the image and diminish noise interference. Subsequently, edge information is amplified by computing the absolute value of the Laplace transform output. Following this, a straight line detection kernel is introduced for a secondary convolution operation, and the 'Euclidean norm' of the outcome is computed to further accentuate the edge characteristics. Ultimately, circuit edges are precisely extracted through the application of local threshold segmentation technology. Experimental results demonstrate that this method enhances anti-interference performance by 1.5 times compared to traditional edge detection algorithms, resulting in improved edge detection effects on PCB board circuits.