Robust profilometer for the measurement of 3-D object shapes based on a regularized phase tracker

A robust pro"lometer is proposed to measure 3-D object shapes based on a regularized phase tracker that is capable of demodulating fringe patterns with a high noise presence and broad bandwidth due to the object shape. As shown herein, the technique acts as an adaptive "lter and is capable of giving the detected phase continuously so that no further unwrapping process is required. Experimental results of real surface pro"les are presented. ( 1999 Published by Elsevier Science Ltd. All rights reserved

Fast estimation of modulo 2pi fringe orientation

A regularized estimator for modulo 2p fringe orientation is presented in this work. As the technique requires to solve locally in the fringe pattern a simple linear system to optimize a regularized cost function, the global estimation of an orientation vector field is performed fast and easily. The performance of this technique is evaluated with synthetic and real fringe patterns

Roundness Estimation of Sedimentary Rocks Using Eliptic Fourier and Deep Neural Networks

Sedimentary rocks analysis is useful in geological science, economic sector, and risk evaluation. Roundness is a morphological parameter that provide information to characterize and classify sedimentary material. Roundness degrees is estimated from the contour of the particle. Waddell (1932) proposed a remarkable method based on the measurement of particle’s curvature. This method is accurate; evertheless, it is not invariant to scale and rotation. This problem can be solved by mapping the contour to the frequencydomain, however, spectral analysis is a difficult task. Based on these two approaches, we propose to use a deep neural network whose input is the elliptical Fourier spectrum and target is roundness proposed by Wadell. The training database consists of 623 realrocks images from some geological phenomena. We have found the neural networks perform very well on the 88.8% of rocks

Roundness Estimation of Sedimentary Rocks Using Eliptic Fourier and Deep Neural Networks

Sedimentary rocks analysis is useful in geological science, economic sector, and risk evaluation. Roundness is a morphological parameter that provide information to characterize and classify sedimentary material. Roundness degrees is estimated from the contour of the particle. Waddell (1932) proposed a remarkable method based on the measurement of particle’s curvature. This method is accurate; evertheless, it is not invariant to scale and rotation. This problem can be solved by mapping the contour to the frequencydomain, however, spectral analysis is a difficult task. Based on these two approaches, we propose to use a deep neural network whose input is the elliptical Fourier spectrum and target is roundness proposed by Wadell. The training database consists of 623 realrocks images from some geological phenomena. We have found the neural networks perform very well on the 88.8% of rocks

Profilometry for the measurement of 3-D object shapes based on regularized filters

Regularized filters RFs. are used in profilometry for the measurement of three-dimensional object shapes. A linear grating pattern projected onto an object is phase-modulated by the 3-D shape. Phase information of the pattern is obtained by a demodulation process using RFs based on Bayesian estimation theory with Markov Random Fields MRFs. as prior models. The technique is fully processed in the space domain and applied in the 2-D case to provide a better separation of the height information from noise. As shown herein, the technique is not so sensitive to the singularities in the pattern image as with common filters used in the spatial synchronous detection. The technique and experimental results of real surface profiles are presented. q1999 Published by Elsevier Science B.V. All rights reserved

Automatic techniques for evaluation of moire deflectograms

In this work we present two methods for the analysis of moire deflectograms. The first method is a Fourier-transform technique. The second method uses a regularization based method. Both methods are applied to realistic deflectograms and their performances are discussed

Synchronous detection technique for temporal fringe pattern analysis

An alternative method for temporal evaluation of fringe patterns is proposed. The method is based on the application of a synchronous detection system for processing the temporal irradiance fluctuations generated when the sensitivity of the optical set-up is changed. The technique requires an easy computing implementation and presents good noise rejection characteristics. In particular, the proposed method does not require to store the whole set of fringe images as it happens with Fourier techniques which allows for a faster data processing. Results of this method proved on synthetic fringe images as well as in real experiments are presente

An alternative differential method of femtosecond pump-probe examination of materials

We describe an alternative method for femtosecond pumpprobe beam examination of energy transport properties of materials. All already reported techniques have several drawbacks which limit precise measurements of reflection coefficient as function of time. A typical problem is present when rough samples are being studied. In this case the pump-beam polarization changes randomly which may produce a spurious signal, drastically reducing the signal to noise ratio. Some proposals to alleviate such problema have been reported, however, they have not been totally satisfactory. The method presented here consists on measuring the difference between the two delays’ signals of the probe-beam. As will be explained, our proposal is free of typical drawbacks. We also propose a numerical method to recover the DR(t)/R curve from the measured data. Numerical simulations show that our proposal is a viable alternative

Regularized quadratic cost function for oriented fringe-pattern filtering

We use the regularization theory in a Bayesian framework to derive a quadratic cost function for denoising fringe patterns. As prior constraints for the regularization problem, we propose a Markov random field model that includes information about the fringe orientation. In our cost function the regularization term imposes constraints to the solution (i.e., the filtered image) to be smooth only along the fringe's tangent direction. In this way as the fringe information and noise are conveniently separated in the frequency space, our technique avoids blurring the fringes. The attractiveness of the proposed filtering method is that the minimization of the cost function can be easily implemented using iterative methods. To show the performance of the proposed technique we present some results obtained by processing simulated and real fringe patterns