Monocular vision-based flatness measurement of steel sheets using fringe projection

Abstract Steel sheet surface flatness serves as a critical quality indicator in modern industrial manufacturing, where its accurate measurement is essential for structural integrity assessment. This paper presents a vision-based measurement system using fringe projection for efficient and reliable flatness inspection. Through Fourier spectrum correction, the system extracts the spatial frequency of fringe patterns projected onto the steel surface and establishes a direct quantitative model between fringe frequency and surface flatness, enabling rapid, precise, and non-contact measurement. Comprehensive simulations and experiments were conducted to analyze key factors influencing system performance, confirming the feasibility and reliability of the proposed approach. Comparative tests against conventional stereoscopic vision demonstrate that the proposed system offers superior robustness to highly reflective surfaces, reduced system complexity, and higher operational efficiency. The core innovation lies in integrating spectral correction with a direct analytical model, which maintains high measurement accuracy while effectively suppressing specular reflections and significantly simplifying the system structure, thereby lowering costs. This provides a practical and innovative solution for online, rapid, and non-contact flatness inspection of steel sheets in industrial settings.