In the context of the gradual sophistication and complexity of electronic products, traditional quality inspection methods have gradually exposed inherent defects. Quality inspection methods based on computer vision technology have become a key driving force for industry innovation due to their highly automated and non-contact advantages. This paper explores the application of computer vision technology in electronic product quality inspection, such as image acquisition and processing, deep learning model construction and optimization. The study found that computer vision technology not only improves the detection efficiency, but also significantly enhances the accuracy of defect recognition, which has broad application prospects.