Detection of Vehicle Body and Geometric Deviations Using Corrected Optical Measurements in Automotive Service Environments

Reliable detection of vehicle body and geometric deviations in automotive service environments remains a challenging task due to unstable measurement conditions and heterogeneous surface properties. While optical diagnostic systems are widely used for non-contact inspection, their accuracy strongly depends on the quality and stability of primary measurements. In this paper, I present methods for detecting vehicle body geometry deviations based on optically measured data obtained after adaptive geometric and photometric correction. The proposed approach operates on stabilized optical measurements and focuses on identifying geometric inconsistencies in body panels and aerodynamic components, including vehicles with modified or non-standard geometry. Experimental results demonstrate that the use of corrected optical measurements significantly improves detection accuracy, repeatability, and robustness compared to uncorrected measurements. The presented methods enable consistent geometric diagnostics under real service conditions and provide a practical basis for subsequent feature-level analysis and decision-making systems in automotive cyber-physical architectures.