Long Luu

Accuracy enhancement of digital image correlation with B-spline interpolation

The interpolation algorithm plays an essential role in the digital image correlation (DIC) technique for shape, deformation, and motion measurements with subpixel accuracies. At the present, little effort has been made to improve the interpolation methods used in DIC. In this Letter, a family of recursive interpolation schemes based on B-spline representation and its inverse gradient weighting version is employed to enhance the accuracy of DIC analysis. Theories are introduced, and simulation results are presented to illustrate the effectiveness of the method as compared with the common bicubic interpolation.

Advanced Geometric Camera Calibration for Machine Vision

In many machine vision applications, a crucial step is to accurately determine the relation between the image of the object and its physical dimension by performing a calibra- tion process. Over time, various calibration techniques have been developed. Nevertheless, the existing methods cannot satisfy the ever-increasing demands for higher accuracy per- formance. In this letter, an advanced geometric camera cali- bration technique which employs a frontal image concept and a hyper-precise control point detection scheme with digital image correlation is presented. Simulation and real experi- mental results have successfully demonstrated the superior of the proposed technique. C 2011 Society of Photo-Optical Instrumen-

Two-dimensional continuous wavelet transform for phase determination of complex interferograms

A robust two-dimensional continuous wavelet transform (2D-CWT) technique for interferogram analysis is presented. To cope with the phase determination ambiguity issue encountered in the analysis of complex interferograms, a phase determination rule is proposed according to the phase distribution continuity, and a frequency-guided scheme is employed to obtain the correct phase distribution following a conventional 2D-CWT analysis. The theories are given in details, and the validity of the proposed technique is verified by computer simulation and real experiments.

Three-dimensional phantoms for curvature correction in spatial frequency domain imaging

The sensitivity to surface profile of non-contact optical imaging, such as spatial frequency domain imaging, may lead to incorrect measurements of optical properties and consequently erroneous extrapolation of physiological parameters of interest. Previous correction methods have focused on calibration-based, model-based, and computation-based approached. We propose an experimental method to correct the effect of surface profile on spectral images. Three-dimensional (3D) phantoms were built with acrylonitrile butadiene styrene (ABS) plastic using an accurate 3D imaging and an emergent 3D printing technique. In this study, our method was utilized for the correction of optical properties (absorption coefficient μa and reduced scattering coefficient μs′) of objects obtained with a spatial frequency domain imaging system. The correction method was verified on three objects with simple to complex shapes. Incorrect optical properties due to surface with minimum 4 mm variation in height and 80 degree in slope were detected and improved, particularly for the absorption coefficients. The 3D phantom-based correction method is applicable for a wide range of purposes. The advantages and drawbacks of the 3D phantom-based correction methods are discussed in details.

Parameter discretization in two-dimensional continuous wavelet transform for fast fringe pattern analysis

The two-dimensional continuous wavelet transform (2D-CWT) technique provides robust processing for digital fringe pattern analysis. To cope with the problem of long computation time, a concept called the cover map is introduced to speed up the 2D-CWT analysis. The cover map is constructed by discretizing the continuous dilation and rotation parameters. The discretized parameters help substantially reduce the processing time without affecting the analysis accuracy. The theories are presented and the validity and effectiveness of the proposed concept are demonstrated by computer simulation and real experiment.

Microfluidics based phantoms of superficial vascular network

Several new bio-photonic techniques aim to measure flow in the human vasculature non-destructively. Some of these tools, such as laser speckle imaging or Doppler optical coherence tomography, are now reaching the clinical stage. Therefore appropriate calibration and validation techniques dedicated to these particular measurements are therefore of paramount importance. In this paper we introduce a fast prototyping technique based on laser micromachining for the fabrication of dynamic flow phantoms. Micro-channels smaller than 20 µm in width can be formed in a variety of materials such as epoxies, plastics, and household tape. Vasculature geometries can be easily and quickly modified to accommodate a particular experimental scenario.

Phase extraction from optical interferograms in presence of intensity nonlinearity and arbitrary phase shifts

We present an advanced technique to retrieve phase from multiple optical interferograms containing intensity nonlinearity and random phase shifts, which are common in practice. The proposed algorithm employs a least-squares iteration scheme to detect harmonics up to the pth order and arbitrary phase shifts simultaneously, and the phase distribution can be accurately extracted from (2p + 1) interferograms. The technique is validated by both computer simulation and real experimental results.

Choice-induced biases in perception

Illusions provide a great opportunity to study how perception is affected by both the observers expectations and the way sensory information is represented1,2,3,4,5,6. Recently, Jazayeri and Movshon7 reported a new and interesting perceptual illusion, demonstrating that the perceived motion direction of a dynamic random dot stimulus is systematically biased when preceded by a motion discrimination judgment. The authors hypothesized that these biases emerge because the brain predominantly relies on those neurons that are most informative for solving the discrimination task8, but then is using the same neural weighting profile for generating the percept. In other words, they argue that these biases are “mistakes” of the brain, resulting from using inappropriate neural read-out weights. While we were able to replicate the illusion for a different visual stimulus (orientation), our new psychophysical data suggest that the above interpretation is likely incorrect: Biases are not caused by a read-out profile optimized for solving the discrimination task but rather by the specific choices subjects make in the discrimination task on any given trial. We formulate this idea as a conditioned Bayesian observer model and show that it can explain the new as well as the original psychophysical data. In this framework, the biases are not caused by mistake but rather by the brains attempt to remain ‘self-consistent’ in its inference process. Our model establishes a direct connection between the current perceptual illusion and the well-known phenomena of cognitive consistency and dissonance9,10.

Assessment of oxygen saturation in retinal vessels of normal subjects and diabetic patients with and without retinopathy using Flow Oximetry System

PURPOSE To assess oxygen saturation (StO2) in retinal vessels of normal subjects and diabetic patients with and without retinopathy using the modified version of the Flow Oximetry System (FOS) and a novel assessment software. METHODS The FOS and novel assessment software were used to determine StO2 levels in arteries and veins located between 1 and 2 mm from the margin of the optic disc and in the macular area. RESULTS Eighteen normal subjects, 15 diabetics without diabetic retinopathy (DM no DR), and 11 with non-proliferative diabetic retinopathy (NPDR) were included in final analysis. The mean [± standard deviation (SD)] StO2 in retinal arteries was 96.9%±3.8% in normal subjects; 97.4%±3.7% in DM no DR; and 98.4%±2.0% in NPDR. The mean venous StO2 was 57.5%±6.8% in normal subjects; 57.4%±7.5% in DM no DR; and 51.8%±6.8% in NPDR. The mean arterial and venous StO2 across the three groups were not statistically different (P=0.498 and P=0.071, respectively). The arterio-venous differences between the three study groups, however, were found to be statistically significant (P=0.015). Pairwise comparisons have demonstrated significant differences when comparing the A-V difference in the NPDR group to either normal subjects (P=0.02) or diabetic patients without DR (P=0.04). CONCLUSIONS The arterio-venous difference was greater, and statistically significant, in patients with NPDR when compared to normal subjects and to patients with diabetes and no retinopathy. The mean venous StO2 was lower, but not statistically significant, in NPDR compared with diabetics without retinopathy and with normal subjects.

Post-decision biases reveal a self-consistency principle in perceptual inference

Making a categorical judgment can systematically bias our subsequent perception of the world. We show that these biases are well explained by a self-consistent Bayesian observer whose perceptual inference process is causally conditioned on the preceding choice. We quantitatively validated the model and its key assumptions with a targeted set of three psychophysical experiments, focusing on a task sequence where subjects first had to make a categorical orientation judgment before estimating the actual orientation of a visual stimulus. Subjects exhibited a high degree of consistency between categorical judgment and estimate, which is difficult to reconcile with alternative models in the face of late, memory related noise. The observed bias patterns resemble the well-known changes in subjective preferences associated with cognitive dissonance, which suggests that the brain’s inference processes may be governed by a universal self-consistency constraint that avoids entertaining ‘dissonant’ interpretations of the evidence.