Content area
In precision manufacturing, machine vision systems utilizing advanced optical technologies and image processing algorithms are crucial for accurately and efficiently detecting surface nonconformities, surpassing manual inspection methods. This study aims to develop a mechanical system with integrated image processing software to enhance quality control in Leica's production by automating defect detection through controlled imaging of components secured on a rotating plate, optimizing alignment, and reducing manual oversight while maintaining high-quality standards.
A comprehensive approach is presented to develop a modular support system for riflescope analysis, emphasizing essential functional requirements such as minimal surface contact, compatibility across various models, and vibration resistance to ensure precise image acquisition. The design prioritizes modularity, ease of assembly, and the prevention of product damage during inspections, integrating advanced components like a motorized mechanism and custom supports to enhance performance and adaptability. Alongside this, the software framework for automated riflescope inspection is detailed, comprising three main components: the control script, the camera activation module, and the image analysis script. Featuring a user-friendly interface that requires identification for access, the software synchronizes camera and motor operations to capture images from multiple angles, storing data locally in an SQL database, while leveraging OpenCV for image processing to detect defects and maintain high precision in quality control.