Розробка методів контролю якості металевих поверхонь для систем технічного зору

Abstract

The paper addresses the relevant problem of quality control of metallic surfaces in the context of Industry 5.0. An information processing method for machine vision systems is proposed, combining spatio-temporal and entropy-based approaches. Modeling and experimental studies were conducted to detect low-contrast defects. The results confirm improved accuracy and reliability of diagnostics, contributing to the development of intelligent quality control systems in industry.