Color fringe-projected technique for measuring dynamic objects based on bidimensional empirical mode decomposition

Abstract

A triple-frequency color fringe-projected technique is presented to measure dynamic objects. Three fringe patterns with a carrier frequency ratio of 1:3:9 are encoded in red, green, and blue channels of a color fringe pattern and projected onto an object's surface. Bidimensional empirical mode decomposition is used for decoupling the cross talk among color channels and for extracting the fundamental frequency components of the three fringe patterns. The unwrapped phase distribution of the high-frequency fringe is retrieved by a three-step phase unwrapping strategy to recover the object's height distribution. Owing to its use of only a single snapshot, the technique is suitable for measuring dynamically changing objects with large discontinuity or spatially isolated surfaces.

Morphological operation-based bi-dimensional empirical mode decomposition for adaptive texture extraction of images

“…In surface interpolation, the radial basis function (RBF) technique [3,5,12] and the triangle-based cubic spline interpolation [4,13] are two typical methods used to interpolate scattered data points. The former uses a global optimizationbased method and has a higher computational cost than the latter [2], which is piecewise cubic interpolation operated locally on triangles of the maxima and minima.…”

Dynamic Phase Measuring Profilometry Based on Tricolor Binary Fringe Encoding Combined Time-Division Multiplexing

“…However, the color cross-talk and the grayscale imbalance problems caused by the color overlapping among the R, G, and B channels one another may lead to extracting the phase-shifting deformed patterns incompletely [17]. Thus, some corresponding color decoupling compensation and grayscale imbalance correction methods are proposed [18][19][20][21]. Cao et al proposed an improved RGB tricolor based fast phase measuring profilometry in which the chroma transfer function (CTF) was introduced to correct the color cross-talk and grayscale imbalance problems among R, G, and B channels [22].…”

“…It worked well, the measuring system may be complicated due to the additional multiple CCD cameras and color filters. Zou et al proposed a color fringe-projected technique based on bidimensional empirical mode decomposition to decouple to color cross-talk among color channels [19]. It did reduce the errors caused by the color cross-talk, but its computational process may be complicated and time consuming.…”

Neural network based color decoupling technique for color fringe profilometry

“…To eliminate the color cross talk, many researchers have come up with some solutions [2,[7][8][9][10][11][12][13][14]. Huang et al [2] tried to quantify the coupling effect by calculating the intensity modulation I ″ , the accuracy of this method is not so high because I ″ is not a constant for the whole pattern; Zhang et al [7] made further study in Huang's method, he added a light filter in front of the lens to improve the performance efficiently; Pan et al [9] put a filter in front of the lens to filter the overlaps in the spectrum as well, but this kind of filter works well only on a 3-CCD camera and is invalid for single CCD cameras.…”

“…She proposed the concept of coupling matrix to deal with the cross talk and used a light splitter to calculate the matrix; Lar Kinell et al [11] calculated the coupling matrix by obtaining the intensity modulation I ″ and decoupled the cross talk using the reverse coupling matrix. Besides, he put an extra filter in front of the camera to achieve a better accuracy; both Zou [12] and Hu [13] proposed mathematical methods to eliminate cross talk: Zou addressed the problem based on bidimensional empirical mode decomposition and Hu introduced a new way to calculate the coupling matrix, both these methods work well but needed complicated computation which took large amount of time. In this paper, we propose a color decoupling method by using neural network.…”