Chiara Di Federico
Dust Detection and Classification: A Machine Vision Approach for Automated Lens Inspection.
Rel. Alessandro Rizzo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2025
Abstract
In recent years, industrial vision has become increasingly important in manufacturing processes, revolutionizing quality control and automation. This multidisciplinary field integrates principles of optics, electronics, computer science and artificial intelligence to develop systems capable of acquiring, processing and interpreting images with greater speed and accuracy than the human eye. Its application enhances production efficiency and product quality while simultaneously reducing operational costs and the risk of errors. In this context, this thesis aims to develop an industrial vision system to support the cosmetic inspection of lenses, specifically to detect dust and distinguish it from actual defects. The project consists of several phases, beginning with the selection of the optimal hardware configuration, which includes choosing the camera, optics and illumination system.
Particular attention was given to illumination, a crucial factor in ensuring sharp and uniform images regardless of the lenses' geometry and color
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