Murat Tahtali

Vibration-based delamination detection in composite beams through frequency changes

Delamination is a common damage in fibre reinforced composite laminates, usually hidden from external view, that can substantially reduce the structural stiffness which changes the dynamic response of the structures such as natural frequencies. Natural frequencies are the most reliable parameters for detecting damage while they do not directly provide information regarding its location and severity. To determine the location and severity of damage, it is necessary to solve the inverse problem using frequency shifts in multiple modes. In this paper, the graphical approach, which was previously employed for estimating two variables of crack (location and size) in isotropic beams, is extended in the current work to estimate the three variables of delamination (interface, span-wise location and size) in anisotropic composite beams from measured frequency shifts. Compared to the use of optimisation or neural network for detection, graphical technique is computationally inexpensive and quick since it solves the inverse problem without iterations or network training. The present approach has been validated using numerical simulation as well as experimental data from modal testing conducted on quasi-isotropic simply supported and cantilever beams. Results show that the proposed graphical technique can be used to assess the location and severity of delamination in composite beams with a high degree of accuracy.

Restoration of Non-Uniformly Warped Images Using a Typical Frame as Prototype

When imaging through the atmosphere, the resulting image contains not only the desired scene, but also the adverse effects of all the turbulent air mass between the camera and the scene. These effects are viewed as a combination of non-uniform blurring and random shifting of each point in the received short-exposure image. Corrections for both aspects of this combined distortion have been tackled reasonably successfully by previous efforts. A potentially more robust method of restoring the geometry is presented, which is also better suited to real-time implementation. The improvements were achieved by redefining the place of the prototype frame and by minimizing the effect of averaging in the processing sequence.

Geometric correction of atmospheric turbulence-degraded video containing moving objects

Long-distance surveillance is a challenging task because of atmospheric turbulence that causes time-varying image shifts and blurs in images. These distortions become more significant as the imaging distance increases. This paper presents a new method for compensating image shifting in a video sequence while keeping real moving objects in the video unharmed. In this approach, firstly, a highly accurate and fast optical flow technique is applied to estimate the motion vector maps of the input frames and a centroid algorithm is employed to generate a geometrically correct frame in which there is no moving object. The second step involves applying an algorithm for detecting real moving objects in the video sequence and then restoring it with those objects unaffected. The performance of the proposed method is verified by comparing it with that of a state-of-the-art approach. Simulation experiments using both synthetic and real-life surveillance videos demonstrate that this method significantly improves the accuracy of image restoration while preserving moving objects.

Restoration of nonuniformly warped images using accurate frame by frame shiftmap accumulation

When imaging through the atmosphere, the resulting image contains not only the desired scene, but also the adverse effects of all the turbulent air mass between the camera and the scene. These effects are viewed as a combination of non-uniform blurring and random shifting of each point in the received short-exposure image. Corrections for both aspects of this combined distortion have been tackled reasonably successfully by previous efforts. A potentially more robust method of restoring the geometry is presented, which is also better suited to real-time implementation. The improvements were achieved by replacing the concept of prototype frame with the sequential registration of each frame with its nearest neighbour and the accurate accumulation of shiftmaps from any one frame to another without redundant calculations.

Graphics processing unit restoration of non-uniformly warped images using a typical frame as prototype

When imaging through the atmosphere, the resulting image contains not only the desired scene, but also the adverse effects of all the turbulent air mass between the camera and the scene. These effects are viewed as a combination of non-uniform blurring and random shifting of each point in the received short-exposure image. Corrections for both aspects of this combined distortion have been tackled reasonably successfully by previous efforts. A potentially more robust method of restoring the geometry is presented, which is also better suited to real-time implementation. The improvements were achieved by redefining the place of the prototype frame and by minimizing the effect of averaging in the processing sequence.

Compressed sensing inspired rapid algebraic reconstruction technique for computed tomography

In this paper, we present an innovative compressive sensing based iterative algorithm for tomographic reconstruction. Back-projection has been customized to make it work even when the projections are not uniformly distributed, and thus ensures a better initial guess to start ART iterations. Contour information of the object has been used efficiently for faster and finer reconstruction. Aiming successful reconstruction with minimum number of iterations, conjugate gradient method that enjoys the full benefit of ART with good initial guess has been used instead of commonly used steepest descent method. Based on the experiments on simulated and real medical images it has been shown that the proposed modality is capable of producing much better reconstruction than the state-of-the-art methods.

Finite element modeling of optic chiasmal compression.

Background: The precise mechanism of bitemporal hemianopia is still not clear. Our study investigated the mechanism of bitemporal hemianopia by studying the biomechanics of chiasmal compression caused by a pituitary tumor growing below the optic chiasm. Methods: Chiasmal compression and nerve fiber interaction in the chiasm were simulated numerically using finite element modeling software. Detailed mechanical strain distributions in the chiasm were obtained to help understand the mechanical behavior of the optic chiasm. Nerve fiber models were built to determine the relative difference in strain experienced by crossed and uncrossed nerve fibers. Results: The central aspect of the chiasm always experienced higher strains than the peripheral aspect when the chiasm was loaded centrally from beneath. Strains in the nasal (crossed) nerve fibers were dramatically higher than in temporal (uncrossed) nerve fibers. Conclusions: The simulation results of the macroscopic chiasmal model are in agreement with the limited experimental results available, suggesting that the finite element method is an appropriate tool for analyzing chiasmal compression. Although the microscopic nerve fiber model was unvalidated because of lack of experimental data, it provided useful insights into a possible mechanism of bitemporal hemianopia. Specifically, it showed that the strain difference between crossed and uncrossed nerve fibers may account for the selective nerve damage, which gives rise to bitemporal hemianopia.

Model-free prediction of atmospheric warp based on artificial neural network

This paper presents the application of artificial neural network for predicting the warping of images of remote objects or scenes ahead of time. The algorithm is based on estimating the pattern of warping of previously captured short-exposure frames through a generalized regression neural network (GRNN) and then predicting the warping of the upcoming frame. A high-accuracy optical flow technique is employed to estimate the dense motion fields of the captured frames, which are considered as training data for the GRNN. The proposed approach is independent of the pixel-oscillatory model unlike the state-of-the-art Kalman filter (KF) approach. Simulation experiments on synthetic and real-world turbulence degraded videos show that the proposed GRNN-based approach performs better than the KF approach in atmospheric warp prediction.

Progressive Restoration of Nonuniformly Warped Images by Shiftmap Prediction Using Kalman Filter

The anisoplanatic warp of imagery through atmospheric turbulence was modelled as a simple oscillator at pixel level and the prediction of restoration shiftmaps using Kalman filter has been successfully demonstrated with robust performance to noise.

An evaluation to design high performance pinhole array detector module for four head SPECT: a simulation study

The purpose of this study is to derive optimized parameters for a detector module employing an off-the-shelf X-ray camera and a pinhole array collimator applicable for a range of different SPECT systems. Monte Carlo simulations using the Geant4 application for tomographic emission (GATE) were performed to estimate the performance of the pinhole array collimators and were compared to that of low energy high resolution (LEHR) parallel-hole collimator in a four head SPECT system. A detector module was simulated to have 48 mm by 48 mm active area along with 1mm, 1.6mm and 2 mm pinhole aperture sizes at 0.48 mm pitch on a tungsten plate. Perpendicular lead septa were employed to verify overlapping and non-overlapping projections against a proper acceptance angle without lead septa. A uniform shape cylindrical water phantom was used to evaluate the performance of the proposed four head SPECT system of the pinhole array detector module. For each head, 100 pinhole configurations were evaluated based on sensitivity and detection efficiency for 140 keV ɣ-rays, and compared to LEHR parallel-hole collimator. SPECT images were reconstructed based on filtered back projection (FBP) algorithm where neither scatter nor attenuation corrections were performed. A better reconstruction algorithm development for this specific system is in progress. Nevertheless, activity distribution was well visualized using the backprojection algorithm. In this study, we have evaluated several quantitative and comparative analyses for a pinhole array imaging system providing high detection efficiency and better system sensitivity over a large FOV, comparing to the conventional four head SPECT system. The proposed detector module is expected to provide improved performance in various SPECT imaging.