The application of optical imaging-based machine vision and image processing in quality control

To improve the efficiency and accuracy of quality control, this article analyzes the application of machine vision and image processing technologies, supported by optical imaging systems, especially in the context of smart city development. Taking supply chain management, logistics sorting and product quality inspection as examples, the article shows how these technologies can drive intelligent optimization of city operations. Through optical sensors and high-resolution imaging components, the system performs image preprocessing and feature extraction, enabling automated defect recognition, dimensional measurement and package integrity inspection—functions that are essential components of smart city logistics and manufacturing ecosystems. The results of the study show that the machine vision system significantly improves inspection efficiency, as the integration of optical modules enhances image clarity and segmentation accuracy, reducing the inspection time for a single product from 8.2 seconds to 2.5 seconds, reducing the false detection rate from 5% to 0.2%, and increasing the number of inspections per hour from 440 to 1,400 pieces. This application ensures quality consistency and reliability of the smart city infrastructure, promoting efficiency and sustainable urban development.