Nondestructive evaluation of FRP composite members using infrared thermography

The objective of this research is to establish infrared thermography as an effective tool for nondestructive evaluation of structural members made of fiber reinforced polymer (FRP) composite materials. The applicability of this method for the detection of subsurface anomalies such as voids, cracks, debonding, and delaminations in concrete bridge decks and pavements and in some configurations of FRP decks has been studied earlier by other researchers. These earlier studies have yielded reasonably satisfactory results though further refinement of the methodology and improvements in the image processing techniques were recommended.;To enhance the effectiveness of the infrared thermography technique, it is important to improve and quantify the contrast in the thermal images. This enables the thermographer to arrive at better conclusions including quantitative estimation of the defect depth. Different methods for analysis of digital infrared images suggested by various researchers were reviewed in this study and recommendations were made for evaluating their applicability for mass-produced FRP composite structural components.;Infrared thermography tests were conducted in the laboratory on various FRP specimens with built-in delaminations. The results showed that the infrared technique can be developed for long term monitoring of FRP structural components. As a part of this research, a field trip was also conducted for detecting the presence of delaminations/debondings in FRP wrapped reinforced concrete bridge columns using infrared thermography. In the field tests, it was possible to detect the locations of delaminations/debondings. These results were in agreement with the tapping test results

Carried baggage detection and recognition in video surveillance with foreground segmentation

Security cameras installed in public spaces or in private organizations continuously record video data with the aim of detecting and preventing crime. For that reason, video content analysis applications, either for real time (i.e. analytic) or post-event (i.e. forensic) analysis, have gained high interest in recent years. In this thesis, the primary focus is on two key aspects of video analysis, reliable moving object segmentation and carried object detection & identification. A novel moving object segmentation scheme by background subtraction is presented in this thesis. The scheme relies on background modelling which is based on multi-directional gradient and phase congruency. As a post processing step, the detected foreground contours are refined by classifying the edge segments as either belonging to the foreground or background. Further contour completion technique by anisotropic diffusion is first introduced in this area. The proposed method targets cast shadow removal, gradual illumination change invariance, and closed contour extraction. A state of the art carried object detection method is employed as a benchmark algorithm. This method includes silhouette analysis by comparing human temporal templates with unencumbered human models. The implementation aspects of the algorithm are improved by automatically estimating the viewing direction of the pedestrian and are extended by a carried luggage identification module. As the temporal template is a frequency template and the information that it provides is not sufficient, a colour temporal template is introduced. The standard steps followed by the state of the art algorithm are approached from a different extended (by colour information) perspective, resulting in more accurate carried object segmentation. The experiments conducted in this research show that the proposed closed foreground segmentation technique attains all the aforementioned goals. The incremental improvements applied to the state of the art carried object detection algorithm revealed the full potential of the scheme. The experiments demonstrate the ability of the proposed carried object detection algorithm to supersede the state of the art method

Astrometry with the Wide-Field InfraRed Space Telescope

The Wide-Field InfraRed Space Telescope (WFIRST) will be capable of delivering precise astrometry for faint sources over the enormous field of view of its main camera, the Wide-Field Imager (WFI). This unprecedented combination will be transformative for the many scientific questions that require precise positions, distances, and velocities of stars. We describe the expectations for the astrometric precision of the WFIRST WFI in different scenarios, illustrate how a broad range of science cases will see significant advances with such data, and identify aspects of WFIRST's design where small adjustments could greatly improve its power as an astrometric instrument.Comment: version accepted to JATI

Topics in Adaptive Optics

Advances in adaptive optics technology and applications move forward at a rapid pace. The basic idea of wavefront compensation in real-time has been around since the mid 1970s. The first widely used application of adaptive optics was for compensating atmospheric turbulence effects in astronomical imaging and laser beam propagation. While some topics have been researched and reported for years, even decades, new applications and advances in the supporting technologies occur almost daily. This book brings together 11 original chapters related to adaptive optics, written by an international group of invited authors. Topics include atmospheric turbulence characterization, astronomy with large telescopes, image post-processing, high power laser distortion compensation, adaptive optics and the human eye, wavefront sensors, and deformable mirrors

Construction of the Scale Aware Anisotropic Diffusion Pyramid With Application to Multi-scale Tracking

This thesis is concerned with the identification of features within two-dimensional imagery. Current acquisition technology is capable of producing very high-resolution images at large frame rates and generating an enormous amount of raw data. Exceeding present signal processing technology in all but the simplest image processing tasks, the visual information contained in these image sequences is tremendous in both spatial and temporal content. A majority of this detail is relatively unimportant for the identification of an object, however, and the motivations for this thesis, at the core, are the study and development of methods that are capable of identifying image features in a highly robust and efficient manor. Biological vision systems have developed methods for coping with high-resolution imagery, and these systems serve as a starting point for designing robust and efficient algorithms capable of identifying features within image sequences. By foveating towards a region of interest, biological systems initially search coarse-scale scene representations and exploit this information to efficiently process finer resolution data. This search procedure is facilitated by the nonlinear distribution of visual sensors within a biological vision system, and the result is a very efficient and robust method for identifying objects. Humans will initially identify peripheral objects as potential regions of interest, acquiring higher-resolution image information by focusing on the region, and deciding if the perceived object is actually present through the use of all available knowledge of the scene

Imaging light transport at the femtosecond scale

Paper, milk, clouds and white paint share a common property: they are opaque disordered media through which light scatters randomly rather than propagating in a straight path. For very thick and turbid media, indeed, light eventually propagates in a ‘diffusive’ way, i.e. similarly to how tea infuses through hot water. Frequently though, a material is neither perfectly opaque nor transparent and the simple diffusion model does not hold. In this work, we developed a novel optical-gating setup that allowed us to observe light transport in scattering media with sub-ps time resolution. An array of unexplored aspects of light propagation emerged from this spatio-temporal description, unveiling transport regimes that were previously inaccessibile due to the extreme time scales involved and the lack of analytical models

Imaging light transport at the femtosecond scale

Paper, milk, clouds and white paint share a common property: they are opaque disordered media through which light scatters randomly rather than propagating in a straight path. For very thick and turbid media, indeed, light eventually propagates in a ‘diffusive’ way, i.e. similarly to how tea infuses through hot water. Frequently though, a material is neither perfectly opaque nor transparent and the simple diffusion model does not hold. In this work, we developed a novel optical-gating setup that allowed us to observe light transport in scattering media with sub-ps time resolution. An array of unexplored aspects of light propagation emerged from this spatio-temporal description, unveiling transport regimes that were previously inaccessibile due to the extreme time scales involved and the lack of analytical models

Advanced Image Acquisition, Processing Techniques and Applications

"Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution