Robust fringe projection measurement based on reference phase reconstruction

Intensity saturation causes partial incorrect intensities in captured images, leading to obvious phase errors in high dynamic range (HDR) phase measuring profilometry. Most of the existing methods require numerous projected patterns or additional hardware equipment to retrieve the 3D shape. This paper proposes a comprehensive saturation-induced phase error correction method by combining the average-phase compensation method applying the four-step phase-shifted(PS) patterns with phase repairment employing a total variation minimization(TVM) model. We first analyzed the periodic characteristic of saturation-induced phase error. The phase error can be efficiently compensated by averaging the initial phase and the auxiliary phase, which was calculated utilizing a set of PS patterns with an initial phase offset of /4. Furthermore, a judgment condition was provided to detect invalid points in overexposed shiny areas whose initial calculated phases were wrong. The corrected phases were repaired utilizing the TVM model from the compensated phase information around the invalid points. Simulations and experiments demonstrated that the proposed method could simultaneously correct the phase for non-uniform high-reflectivity scenes and shiny areas on the surface with high accuracy and relatively few images. The phase error is reduced to nearly 80%.

“…According to [32], the solving process can be cast into the Sylvester matrix equation in the form of AX + XB = C seamlessly, where the parameters are exactly represented as…”

Section: Invalid Phase Repair In Shiny Areamentioning

confidence: 99%

Generic saturation-induced phase-error correction algorithm for phase-measuring profilometry

Tao

et al. 2023

“…Wang and Yang [11] developed a triple N-step phase shifting approach to minimize the nonliear errors of images cuaused by the nonlinear response of measurement system. In addition, for industrial application scenarios, a new method was introduced to reduce errors caused by reference plane deviation on FPP measurement results [12]. For the online measurment of step-shape workpieces and gear workpieces, the proposed method showed good performance.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of variant shifting-phase coding method based on noise error model

Wu,

Mu,

Cheng

et al. 2024

Phase shifting algorithm, which is well-known for its high-accuracy and high-resolution, plays a crucial role in fringe projection profilometry. A class of variant shifting-phase coding method (VSPCM) has been proposed for high-speed 3D measurement. The three kinds of VSPCM include the inner shifting-phase method (ISPM), the intensity-coded method (ICM) and the modified Carré algorithm (MCA). These methods project only four patterns avoiding the need for extra images, yet achieve accuracy comparable to the classical three-frequency heterodyne method. In VSPCM, the shifting-phase, as a key code-word for phase unwrapping, is encoded as a variable value. In practice, the noise and the encoding of shifting-phase have varying degrees of impact on the performance of these methods. But the coded ranges of the shifting-phase were previouly empirical values. Besides, there are no studies related to these factors, and also a lack of comparative researches on such methods. This paper compares three kinds of VSPCM for the first time. We derive the noise error models for shifting-phase and wrapped phase in three methods and examine the impact of variant shifting-phase on fringe orders and wrapped phase in these methods. We find that the abnormal shifting-phase errors predominantly cause fringe orders errors. Fortunately, median filtering can effectively handle shifting-phase errors to ensure successful phase unwrapping. To improve their accuracy, we also deduce that the optimal shifting-phase encoding range is [-77°, 77°] for ISPM, and is [-61°, 61°] for ICM, and is [34°, 74°] for MCA. For wrapped phase errors, the distributions of ICM and MCA exhibit a U-shaped distribution, while ISPM demonstrates a uniform distribution. Based on theoretical analysis and experiment results, this paper gives recommendations for better use of these methods to boost their accuracy and offers valuable guidance for selecting an appropriate variant shifting-phase coding method under the specific measurement requirements.

“…These scenarios urgently demand for full-scale 3D measurement, e.g. dental medical modeling, biological tissue detection, and precision reverse engineering [6][7][8][9]. The entire geometric model 3D reconstruction can be achieved by registering measured results from multi-perspective.…”

Section: Introductionmentioning

confidence: 99%

Handheld structured light system for panoramic 3D measurement in mesoscale

Su,

Tan,

et al. 2024

The measurement of complete 3D topography in mesoscale plays a vital role in high-precision reverse engineering, oral medical modeling, circuit detection, etc. Traditional structured light systems are limited to measuring 3D shapes from a single perspective. How to achieve high-quality mesoscopic panoramic 3D measurement remains challenging, especially in complex measured scenarios such as dynamic measurement, scattering medium, and high reflectance. To overcome these problems, we develop a handheld mesoscopic panoramic 3D measurement system for such complex scenes together with the fast point-cloud-registration and accurate 3D-reconstruction, where a motion discrimination mechanism is designed to ensure that the captured fringe is in a quasi-stationary case by avoiding the motion errors caused during fringe scanning; a deep neural network is utilized to suppressing the fringe-degradation caused by scattering mediums resulting to significantly improves the quality of the 3D point cloud; a strategy based on phase averaging is additionally proposed to simultaneously correct the saturation-induced errors and gamma nonlinear errors. Finally, the proposed system with a multi-threaded data processing framework is further developed to verify the proposed method and the corresponding experiments verify its feasibility.