Automatic optimization of projection intensity for high dynamic range 3D surface measurement

Abstract

Stripe projection profilers are widely used in many fields because of their high speed, high accuracy, and clear surface textures. In the structured light projection method, the complex reflectance distribution on the surface of the high-dynamic-range objective is an important factor that affects the measurement accuracy, as it can result in image over- and under-exposure. In this study, a method is proposed to adaptively determine the number of stripe patterns and the corresponding number of light intensities of the stripe patterns based on the complex reflectance of the surface of the object being measured. A multi threshold Otsu algorithm is used to classify the histogram of the surface reflectance distribution of the measured object, and several sets of stripe patterns with optimal light intensity are generated according to the light intensity response function. The original stripe patterns acquired at different light intensities are synthesized pixel by pixel into a high dynamic range (HDR) stripe image, and a four-step phase-shifting algorithm is used to obtain the unwrapped phase from the synthesized image. Experimental results show that this method can accurately measure the target of a surface-reflectance-transformed HDR.