To achieve the accurate detection of placement pose deviations of communication module products during automated testing, we propose a detection method based on machine vision and overexposure features. This method regulates the exposure parameters of an industrial camera to establish special detection conditions: when the product is correctly positioned, the surface image of the communication module is in an overexposed state, and after binarization processing, the number of black pixels is zero; when the product is misaligned, the surface image is in a normally exposed state, and after the same image processing, the number of black pixels is significantly greater than zero. By comparing the differences in the number of black pixels between the two states in real time, the pose deviations of the product can be precisely identified. This method utilizes the overexposure imaging characteristics to construct a detection criterion with significant distinguishability. Experimental validation in both laboratory and real-world environments demonstrates that this method can accurately detect pose deviations of products during automated testing, effectively improving the stability of automated testing lines.