High dynamic range 3D measurements with fringe projection profilometry: a review

Abstract

In optical metrology, fringe projection is considered to be one of the most reliable techniques for recovering the shape of objects. For this technique, however, it is challenging to measure objects with a large variation in surface reflectivity, e.g. a scenario containing both dark and bright objects. Researchers have thus developed various approaches to high dynamic range (HDR) three-dimensional (3D) measurements over the years. In this paper, we present an overview of these techniques, as well as a new and definitive classification for them. We implement a set of representative techniques to measure objects with different characteristics of reflectance and discuss the advantages and constraints of the techniques according to the comparative results. Moreover, challenging problems and future research directions are discussed to advance HDR 3D measurement techniques.

Adaptive Binocular Fringe Dynamic Projection Method for High Dynamic Range Measurement

“…Due to the advantages of high speed, high accuracy, and full light field, fringe projection profilometry (FPP) based on structured light sensor [1,2,3] has become the most promising three-dimensional (3D) data acquisition technique in many fields, such as quality control [4,5,6], reverse engineering [7,8], and others [9,10,11]. Generally, the system of fringe projection profilometry consists of one camera and one projector.…”

“…The 3D data can provide an effective evaluation mean for surface inspection, precision manufacturing, automatic assembly, and other fields. The literature [1,2,3,6] shows that FPP is more suitable for diffuse reflective surfaces and the surface reflectance changes little. However, when objects with high dynamic range (HDR) were measured directly by FPP, some saturated regions will appear in fringe images, which challenge the completeness of phase information and measurement accuracy.…”

“…Addressing that it is difficult to improve the dynamic range by hardware for the most camera sensors [6], many experts have carried out a series of approaches to solve the HDR measurement problem. The methods can be divided into several categories: multi-exposure method [12,13,14], light intensity adjustment method [15,16], color invariance method [17,18,19], polarization method [20,21,22], adaptive fringe pattern method [23,24,25,26,27], and others [28,29].…”

Hybrid 3D Shape Measurement Using the MEMS Scanning Micromirror

“…However, FPP assumes that the measuring surface exhibits a diffuse reflection and usually considers low-reflective (dark) and highlighted (specular reflection) areas as outliers. These regions can completely block any fringe patterns, which results in the loss of depth information [14,15,16]. To address this problem, some solutions are presented.…”

Microscopic 3D measurement of shiny surfaces based on a multi-frequency phase-shifting scheme

“…Shiny surfaces are highly reflective, and thus the light intensity cannot be transformed linearly because of the limited dynamic range of digital cameras. One of the stateof-the-art techniques for this situation is called the highdynamic range 3D shape measurement [10], which can be classified into two categories: equipment-based techniques and algorithm-based techniques. For the group of the equipment-based techniques, optimal parameters of the equipment, e.g., the exposure time of the camera [11,12,13] or the projector [14,15,16,17] are desired to help capture visible fringe at both shiny and dark surfaces.…”