Absolute phase plays a crucial role in various applications, including camera or projector calibration, stereo matching, structured light measurement, and fringe projection profilometry (FPP). Recently, significant progress has been made in the development of deep learning-based approaches for absolute phase recovery. Many deep neural networks have been created, improved, or directly integrated into the phase retrieval procedure. Analyzing these methods, a common trend is observed in the sequential calculation of wrapped phase, fringe order, and absolute phase. The accuracy of previous results has a direct impact on the subsequent steps, leading to potential error accumulation and reduced recovery speed. To address these challenges, we propose an end-to-end deep learning method based on Res-UNet that directly predicts the absolute phase from a single fringe image without any additional fringe patterns. The presented approach simplifies the procedure of phase unwrapping and overcomes limitations of existing techniques. To note that, to save cost and labor for training the Res-UNet, a novel and virtual digital fringe project system with 3D Studio Max is also established for generating data close to reality. Experiments have been carried out to validate the performances of the proposed method.
In the fringe projection profilometry (FPP), traditionally, no clear mathematical expression was developed to design the sinusoidal fringe patterns for various objects. For this reason, we present an adaptive algorithm to generate the optimum fringe patterns with an oriented bounding box (OBB) and homography transform. Firstly, the features of various objects, which are segmented with deep learning network Mask R-CNN, are represented by the spindle orientation and length of the OBB. Secondly, the adaptive fringe patterns in the field of view of a camera are generated by the fusion with the OBB and the mathematical expression of conventional intensity fringe patterns. Finally, the fringe patterns in the field of view of a camera is transformed into the in the field of view of a projector by homography. Experiments have been carried out to validate the performances of the proposed method.
Absolute phase plays a very important role for many applications. At present, various techniques have been exhaustively developed for absolute phase recovery. There are three major categories: spatial phase unwrapping, temporal phase unwrapping and deep learning techniques. Analyzing from these methods, a commonality is limited into the procedure of absolute phase recovery. Namely, the conventional algorithms yield to calculate wrapped phase, fringe order and absolute phase in turn. There is a closer dependency between the accuracy of the previous results and the next ones. So more serious errors could accumulate from this computation procedure, meanwhile the recovery speed is decreased. For this reason, we present an end-to-end method to obtain the absolute phase maps by projecting only two-step specially intensity-coded fringe patterns. Unlike the above-mentioned techniques, we can not only compute the wrapped phases from two fringe images, but also decode the corresponding fringe orders simultaneously from two fringe images without any additional patterns. The presented method breaks the limitation and simplifies the procedure of phase unwrapping. Simulations have been carried out to validate the feasibility of the proposed method.
Wrapped phase extraction is an essential process for the retrieval of absolute phase and even the computation of object height information in fringe projection profilometry. Over the past few decades, tremendous efforts have been devoted to developing various techniques for computing wrapped phase. By comparison, four-step phase-shifting techniques play an important vehicle for obtaining the wrapped phase of 3D objects. At present, a variety of four-step phase-shifting algorithms show the comprehensive mathematical deduction and their theories are very clear. Analysis from the perspective of theoretical integrity, however, the phase-shifting techniques lack the exploration of arbitrary phase shift. In view of this, inspired by the prosthaphaeresis in trigonometric, we present a novel four-step phase-shifting algorithm. The proposed method includes 16 kinds of four-step phase-shifting fringe combination and corresponding calculation formula of wrapped phase, which are deduced with two frames fringe images of sines and two ones of cosines. Furthermore, simulations and experiments have been carried out to reveal the influence law of variable phase shift on the performance of these approaches.
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