A method for high dynamic range 3D color modeling of objects through a color camera

Abstract

This paper proposes a novel method for enhancing the dynamic range of structured-light cameras to solve the problem of highlight that occurs when 3D modeling highly reflective objects using the structured-light method. Our method uses the differences in quantum efficiency between R, G, and B pixels in the color image sensor of a monochromatic laser to obtain structured-light images of an object under test with different luminance values. Our approach sacrifices the resolution of the image sensor to increase the dynamic range of the vision system. Additionally, to enhance our system, we leverage the backgrounds of structured-light stripe pattern images to restore the color information of measured objects, whereas the background is often removed as noise in other 3D reconstruction systems. This reduces the number of cameras required for 3D reconstruction and the matching error between point clouds and color data. We modeled both highly reflective and non-highly reflective objects and achieved satisfactory results.

A Polarized Structured Light Method for the 3D Measurement of High-Reflective Surfaces

“…This method is equivalent to adding an optical filter to deal with the problem of high reflection. In [12], the difference in sensitivity efficiency of monochromatic laser under the RGB channel of color sensor is used to obtain images with different brightness values, which are fused to obtain images with high dynamic range for reconstruction. This method utilizes optical filters on the color sensor and HDR technology to accomplish high-dynamic-range 3D reconstruction.…”

“…For the problem of highlight in SL method, the existing solutions mainly include adaptive projection intensity, multiple exposures, multi-view method, and the use of optical filters [8][9][10][11][12]. These methods can alleviate the reconstruction issue caused by high-reflective surfaces to some extent.…”