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In order to improve the detection efficiency and accuracy of aerospace and military electronic products, an electronic component detection system based on machine vision is designed. By researching effective positioning and detection algorithms, the function of detecting the wedding accuracy of components with different specification and models on Printed Circuit Board (PCB) is realized. The improved Hough detection algorithm is employed to identify the position of marking point, which combined with process documents can be used to search the location of components. And according to dimensions, the single component image is segmented by drawing Region of Interest (ROI) boxes. Finally, Speed Up Robust Features (SURF) algorithm is employed to complete feature extraction and method based on the ratio of nearest neighbor to next nearest neighbor is employed to do image matching，the accuracy is 85%. Besides, the matching results are tested when illumination changes and affine transformation of electronic components occur. Results indicate that in different experimental conditions such as displacement transformation, angle transformation, scaling transformation, illumination transformation, and so on, the algorithm can match the template image in the target region, which has good matching effect, the accuracy is 90%. The correctness detection of components is realized with good accuracy and stability.