Shape-Adaptive Lighting for Complex Geometries in Automated Visual Inspection

Abstract

Automating visual inspection has the potential to remove the current bottleneck of burdensome and subjective manual inspection in precision manufacturing. However, complex geometries of parts hinder uniform illumination, and high reflectivity challenges accurate focusing for digital visual data collection. This paper provides a novel method to distribute consistent illuminance for quality image data collection over complex-shaped, highly reflective surfaces. The central approach entails using arrays of independently controlled light sources to generate different lighting patterns, structures, and colors. Such results consider the geometry and 3D pose of objects in the environment and the surface topography of the work-piece to be inspected, leading to greater imaging qualities for precision inspection. This paper discusses the mathematical problem formulation, the analytic solution, the optimality of the proposed shape-adaptive lighting, and experimental results in imaging curved parts common in precision manufacturing.