8 research outputs found
DeepOrientation: convolutional neural network for fringe pattern orientation map estimation
Fringe pattern based measurement techniques are the state-of-the-art in
full-field optical metrology. They are crucial both in macroscale, e.g., fringe
projection profilometry, and microscale, e.g., label-free quantitative phase
microscopy. Accurate estimation of the local fringe orientation map can
significantly facilitate the measurement process on various ways, e.g., fringe
filtering (denoising), fringe pattern boundary padding, fringe skeletoning
(contouring/following/tracking), local fringe spatial frequency (fringe period)
estimation and fringe pattern phase demodulation. Considering all of that the
accurate, robust and preferably automatic estimation of local fringe
orientation map is of high importance. In this paper we propose novel numerical
solution for local fringe orientation map estimation based on convolutional
neural network and deep learning called DeepOrientation. Numerical simulations
and experimental results corroborate the effectiveness of the proposed
DeepOrientation comparing it with the representative of the classical approach
to orientation estimation called combined plane fitting/gradient method. The
example proving the effectiveness of DeepOrientation in fringe pattern
analysis, which we present in this paper is the application of DeepOrientation
for guiding the phase demodulation process in Hilbert spiral transform. In
particular, living HeLa cells quantitative phase imaging outcomes verify the
method as an important asset in label-free microscopy
On Fresnelets, interference fringes, and digital holography
In this thesis, we describe new approaches and methods for reconstructing complex-valued wave fields from digital holograms. We focus on Fresnel holograms recorded in an off-axis geometry, for which operational real-time acquisition setups readily exist. The three main research directions presented are the following. First, we derive the necessary tools to port methods and concepts of wavelet-based approaches to the field of digital holography. This is motivated by the flexibility, the robustness, and the unifying view that such multiresolution procedures have brought to many applications in image processing. In particular, we put emphasis on space-frequency processing and sparse signal representations. Second, we propose to decouple the demodulation from the propagation problem, which are both inherent to digital Fresnel holography. To this end, we derive a method for retrieving the amplitude and phase of the object wave through a local analysis of the hologram's interference fringes. Third, since digital holography reconstruction algorithms involve a number of parametric models, we propose automatic adjustment methods of the corresponding parameters. We start by investigating the Fresnel transform, which plays a central role in both the modeling of the acquisition procedure and the reconstruction of complex wave fields. The study of the properties that are central to wavelet and multiresolution analysis leads us to derive Fresnelets, a new family of wavelet-like bases. Fresnelets permit the analysis of holograms with a good localization in space and frequency, in a way similar to wavelets for images. Since the relevant information in a Fresnel off-axis hologram may be separated both in space and frequency, we propose an approach for selectively retrieving the information in the Fresnelet domain. We show that in certain situations, this approach is superior to others that exclusively rely on the separation in space or frequency. We then derive a least-squares method for the estimation of the object wave's amplitude and phase. The approach, which is reminiscent of phase-shifting techniques, is sufficiently general to be applied in a wide variety of situations, including those dictated by the use of microscopy objectives. Since it is difficult to determine the reconstruction distance manually, we propose an automatic procedure. We take advantage of our separate treatment of the phase retrieval and propagation problems to come up with an algorithm that maximizes a sharpness metric related to the sparsity of the signal's expansion in distance-dependent Fresnelet bases. Based on a simulation study, we suggest a number of guidelines for deciding which algorithm to apply to a given problem. We compare existing and the newly proposed solutions in a wide variety of situations. Our final conclusion is that the proposed methods result in flexible algorithms that are competitive with preexisting ones and superior to them in many cases. Overall, they may be applied in a wide range of experimental situations at a low computational cost
Phase extraction of non-stationary signals produced in dynamic interferometry involving speckle waves
It is now widely acknowledged, among communities of researchers and engineers of very different horizons, that speckle interferometry (SI) offers powerful techniques to characterize mechanical rough surfaces with a submicronic accuracy in static or quasi-static regime, when small displacements are involved (typically several microns or tens of microns). The issue of dynamic regimes with possibly large deformations (typically several hundreds of microns) is still topical and prevents an even more widespread use of speckle techniques. This is essentially due to the lack of efficient processing schemes able to cope with non-stationary AM-FM interferometric signals. In addition, decorrelation-induced phase errors represent an hindrance to accurate measurement when such large displacements and classical fringe analysis techniques are considered. This work is an attempt to address those issues and to endeavor to make the most of speckle interferometry signals. Our answers to those problems are located on two different levels. First of all, we adopt the temporal analysis approach, i.e. the analysis of the temporal signal of each pixel of the sensor area used to record the interferograms. A return to basics of phase extraction is operated to properly identify the conditions under which the computed phase is meaningful and thus give some insight on the physical phenomenon under analysis. Due to their intrinsic non-stationary nature, a preprocessing tool is missing to put the SI temporal signals in a shape which ensures an accurate phase computation, whichever technique is chosen. This is where the Empirical Mode Decomposition (EMD) intervenes. This technique, somehow equivalent to an adaptive filtering technique, has been studied and tailored to fit with our expectations. The EMD has shown a great ability to remove efficiently the random fluctuating background intensity and to evaluate the modulation intensity. The Hilbert tranform (HT) is the natural quadrature operator. Its use to build an analytical signal from the so-detrended SI signal, for subsequent phase computation, has been studied and assessed. Other phase extraction techniques have been considered as well for comparison purposes. Finally, our answer to the decorrelation-induced phase error relies on the well-known result that the higher the pixel modulation intensity, the lower the random phase error. We took benefit from this result â not only linked to basic SNR considerations, but more specifically to the intrinsic phase structure of speckle fields â with a novel approach. The regions within the pixel signal history classified as unreliable because under-modulated, are purely and simply discarded. An interpolation step with the Delaunay triangulation is carried out with the so-obtained non-uniformly sampled phase maps to recover a smooth phase which relies on the most reliable available data. Our schemes have been tested and discussed with simulated and experimental SI signals. We eventually have developed a versatile, accurate and efficient phase extraction procedure, perfectly able to tackle the challenge of dynamic behaviors characterization, even for displacements and/or deformations beyond the classical limit of the correlation dimensions
An experimental study of the feasibility of phaseâbased video magnification for damage detection and localisation in operational deflection shapes
Optical measurements from highâspeed, highâdefinition video recordings can be used to define the fullâfield dynamics of a structure. By comparing the dynamic responses resulting from both damaged and undamaged elements, structural health monitoring can be carried out, similarly as with mounted transducers. Unlike the physical sensors, which provide pointâwise measurements and a limited number of output channels, highâquality video recording allows very spatially dense information. Moreover, video acquisition is a noncontact technique. This guarantees that any anomaly in the dynamic behaviour can be more easily correlated to damage and not to added mass or stiffness due to the installed sensors.
However, in realâlife scenarios, the vibrations due to environmental input are often so small that they are indistinguishable from measurement noise if conventional imageâbased techniques are applied. In order to improve the signalâtoânoise ratio in lowâamplitude measurements, phaseâbased motion magnification has been recently proposed.
This study intends to show that modelâbased structural health monitoring can be performed on modal data and time histories processed with phaseâbased motion magnification, whereas unamplified vibrations would be too small for being successfully exploited. All the experiments were performed on a multidamaged box beam with different damage sizes and angles
Image-Based Fracture Mechanics with Digital Image Correlation and Digital Volume Correlation
Analysis that requires human judgement can add bias which may, as a result, increase uncertainty. Accurate detection of a crack and segmentation of the crack geometry is beneficial to any fracture experiment. Studies of crack behaviour, such as the effect of closure, residual stress in fatigue or elastic-plastic fracture mechanics, require data on crack opening displacement. Furthermore, the crack path can give critical information of how the crack interacts with the microstructure and stress fields. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) have been widely accepted and routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. However, current practise for the extraction of crack parameters from displacement fields usually requires manual methods and are quite onerous, particularly for large amounts of data.
This thesis introduces the novel application of Phase Congruency-based Crack Detection (PC-CD) to automatically detect and characterise cracks from displacement fields.
Phase congruency is a powerful mathematical tool that highlights a discontinuity more efficiently than gradient based methods. Phase congruencyâs invariance to the magnitude of the discontinuity and its state-of-the-art de-noising method, make it ideal for the application to crack tip displacement fields. PC-CDâs accuracy is quantified and benchmarked using both theoretical and virtual displacement fields. The accuracy of PC-CD is evaluated and compared with conventional, manual computation methods such as Heaviside function fitting and gradient based methods. It is demonstrated how PC-CD can be coupled with a new method that is based on the conjoint use of displacement fields and finite element analysis to extract the strain energy release rate of cracks automatically. The PC-CD method is extended to volume displacement fields (VPC-CD) and semi-autonomously extracts crack surface, crack front and opening displacement through the thickness. As a proof of concept, PC-CD and VPC-CD are applied to a range of fracture experiments varying in material and fracture behaviour: two ductile and one quasi-brittle for surface displacement measurements; and two quasi-brittle and one ductile for volume measurements. Using the novel PC-CD and VPC-CD analyses, the crack geometry is obtained fully automatically and without any user judgement or intervention. The geometrical parameters extracted by PC-CD and VPC-CD are validated experimentally through other tools such as: optical microscope measurements, high resolution fractography and visual inspection
Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication
A new theory of mammalian hearing is presented, which accounts for the
auditory image in the midbrain (inferior colliculus) of objects in the
acoustical environment of the listener. It is shown that the ear is a temporal
imaging system that comprises three transformations of the envelope functions:
cochlear group-delay dispersion, cochlear time lensing, and neural group-delay
dispersion. These elements are analogous to the optical transformations in
vision of diffraction between the object and the eye, spatial lensing by the
lens, and second diffraction between the lens and the retina. Unlike the eye,
it is established that the human auditory system is naturally defocused, so
that coherent stimuli do not react to the defocus, whereas completely
incoherent stimuli are impacted by it and may be blurred by design. It is
argued that the auditory system can use this differential focusing to enhance
or degrade the images of real-world acoustical objects that are partially
coherent. The theory is founded on coherence and temporal imaging theories that
were adopted from optics. In addition to the imaging transformations, the
corresponding inverse-domain modulation transfer functions are derived and
interpreted with consideration to the nonuniform neural sampling operation of
the auditory nerve. These ideas are used to rigorously initiate the concepts of
sharpness and blur in auditory imaging, auditory aberrations, and auditory
depth of field. In parallel, ideas from communication theory are used to show
that the organ of Corti functions as a multichannel phase-locked loop (PLL)
that constitutes the point of entry for auditory phase locking and hence
conserves the signal coherence. It provides an anchor for a dual coherent and
noncoherent auditory detection in the auditory brain that culminates in
auditory accommodation. Implications on hearing impairments are discussed as
well.Comment: 603 pages, 131 figures, 13 tables, 1570 reference
Graduate Catalog, 1996-1999, New Jersey Institute of Technology
https://digitalcommons.njit.edu/coursecatalogs/1003/thumbnail.jp