Pixel level data-dependent triangulation with its applications

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Validation of a Confocal Light Sheet Microscope using Push Broom Translation for Biomedical Applications

There exists a need for research of optical methods capable of image cytometry suitable for point-of-care technology. To propose am optical approach with no moving parts for simplification of mechanical components for the further development of the technology to the poin-of-care, a linear sensor with push broom translation method. Push broom translation is a method of moving objects by the sensor for an extended field of view. A polydimethylsiloxane (PDMS) microfluidic chamber with a syringe pump was used to deliver objects by the sensor. The volumetric rate of the pump was correlated to the integration time of the sensor to ensure images were realistically being formed, termed aspect ratio. An electro-chemical microfluidic system was then also investigated, redox-magnetohydrodynamics (R-MHD), to eliminate the mechanical syringe pump which showed deviations in linear speeds at the specimen plane. To image with adequate signal to background ratio within the deep chamber of the R-MHD device, an epitaxial light sheet confocal microscope (e-LSCM) was used to improve axial resolution. The linear sensor, having small pixels, blocked out-of-plane light while eliminating the need for a mechanical aperture which is used for traditional point-scanning confocal microscopy. The particular linear sensor used has binning modes that were used to vary the axial resolution by increasing the sensor aperture. This approach was validated by using a mirror translated in the axial direction and measuring remitted light intensity. The resulting curve estimated the real axial resolution of the microscope, which compared favorably to theoretical values. The R-MHD and the e-LSCM were then synchronized to perform continuous imaging of fluorescent microspheres and cells in suspension. This study combines epitaxial light sheet confocal microscopy and electro-chemical microfluidics as a robust approach which could be used in future point-of-care image cytometry applications

Simulation-based Planning of Machine Vision Inspection Systems with an Application to Laser Triangulation

Nowadays, vision systems play a central role in industrial inspection. The experts typically choose the configuration of measurements in such systems empirically. For complex inspections, however, automatic inspection planning is essential. This book proposes a simulation-based approach towards inspection planning by contributing to all components of this problem: simulation, evaluation, and optimization. As an application, inspection of a complex cylinder head by laser triangulation is studied

A Compact Camera with a Reconfigurable Real-time Embedded Image Processor for Pharmaceutical Capsule Inspections

The following thesis presents the system requirements, design methodology, final hardware design and system integration of a custom digital camera for high-speed pharmaceutical capsule inspections. The primary goals of the camera design were to minimize the cost of the device and to have a flexible design that could be easily upgraded in the future. For this application, a 3.1 mega pixel CMOS image sensor was used with a USB 2.0 interface. In addition, the custom camera can pre-process image data in an embedded, reconfigurable real-time image processor implemented in a FPGA. All data processing in the camera occurs with only buffering four rows of an image, eliminating the need for RAM on the device and lowering the overall cost. The final design was manufactured and implemented into a complete inspection system which used 16 of these cameras to inspect up to 60 000 capsules per second

Towards Highly-Integrated Stereovideoscopy for \u3ci\u3ein vivo\u3c/i\u3e Surgical Robots

When compared to traditional surgery, laparoscopic procedures result in better patient outcomes: shorter recovery, reduced post-operative pain, and less trauma to incisioned tissue. Unfortunately, laparoscopic procedures require specialized training for surgeons, as these minimally-invasive procedures provide an operating environment that has limited dexterity and limited vision. Advanced surgical robotics platforms can make minimally-invasive techniques safer and easier for the surgeon to complete successfully. The most common type of surgical robotics platforms -- the laparoscopic robots -- accomplish this with multi-degree-of-freedom manipulators that are capable of a diversified set of movements when compared to traditional laparoscopic instruments. Also, these laparoscopic robots allow for advanced kinematic translation techniques that allow the surgeon to focus on the surgical site, while the robot calculates the best possible joint positions to complete any surgical motion. An important component of these systems is the endoscopic system used to transmit a live view of the surgical environment to the surgeon. Coupled with 3D high-definition endoscopic cameras, the entirety of the platform, in effect, eliminates the peculiarities associated with laparoscopic procedures, which allows less-skilled surgeons to complete minimally-invasive surgical procedures quickly and accurately. A much newer approach to performing minimally-invasive surgery is the idea of using in-vivo surgical robots -- small robots that are inserted directly into the patient through a single, small incision; once inside, an in-vivo robot can perform surgery at arbitrary positions, with a much wider range of motion. While laparoscopic robots can harness traditional endoscopic video solutions, these in-vivo robots require a fundamentally different video solution that is as flexible as possible and free of bulky cables or fiber optics. This requires a miniaturized videoscopy system that incorporates an image sensor with a transceiver; because of severe size constraints, this system should be deeply embedded into the robotics platform. Here, early results are presented from the integration of a miniature stereoscopic camera into an in-vivo surgical robotics platform. A 26mm X 24mm stereo camera was designed and manufactured. The proposed device features USB connectivity and 1280 X 720 resolution at 30 fps. Resolution testing indicates the device performs much better than similarly-priced analog cameras. Suitability of the platform for 3D computer vision tasks -- including stereo reconstruction -- is examined. The platform was also tested in a living porcine model at the University of Nebraska Medical Center. Results from this experiment suggest that while the platform performs well in controlled, static environments, further work is required to obtain usable results in true surgeries. Concluding, several ideas for improvement are presented, along with a discussion of core challenges associated with the platform. Adviser: Lance C. Pérez [Document = 28 Mb

Digital forensic techniques for the reverse engineering of image acquisition chains

In recent years a number of new methods have been developed to detect image forgery. Most forensic techniques use footprints left on images to predict the history of the images. The images, however, sometimes could have gone through a series of processing and modification through their lifetime. It is therefore difficult to detect image tampering as the footprints could be distorted or removed over a complex chain of operations. In this research we propose digital forensic techniques that allow us to reverse engineer and determine history of images that have gone through chains of image acquisition and reproduction. This thesis presents two different approaches to address the problem. In the first part we propose a novel theoretical framework for the reverse engineering of signal acquisition chains. Based on a simplified chain model, we describe how signals have gone in the chains at different stages using the theory of sampling signals with finite rate of innovation. Under particular conditions, our technique allows to detect whether a given signal has been reacquired through the chain. It also makes possible to predict corresponding important parameters of the chain using acquisition-reconstruction artefacts left on the signal. The second part of the thesis presents our new algorithm for image recapture detection based on edge blurriness. Two overcomplete dictionaries are trained using the K-SVD approach to learn distinctive blurring patterns from sets of single captured and recaptured images. An SVM classifier is then built using dictionary approximation errors and the mean edge spread width from the training images. The algorithm, which requires no user intervention, was tested on a database that included more than 2500 high quality recaptured images. Our results show that our method achieves a performance rate that exceeds 99% for recaptured images and 94% for single captured images.Open Acces

Monitoring 3D vibrations in structures using high resolution blurred imagery

This thesis describes the development of a measurement system for monitoring dynamic tests of civil engineering structures using long exposure motion blurred images, named LEMBI monitoring. Photogrammetry has in the past been used to monitor the static properties of laboratory samples and full-scale structures using multiple image sensors. Detecting vibrations during dynamic structural tests conventionally depends on high-speed cameras, often resulting in lower image resolutions and reduced accuracy. To overcome this limitation, the novel and radically different approach presented in this thesis has been established to take measurements from blurred images in long-exposure photos. The motion of the structure is captured in an individual motion-blurred image, alleviating the dependence on imaging speed. A bespoke algorithm is devised to determine the motion amplitude and direction of each measurement point. Utilising photogrammetric techniques, a model structure s motion with respect to different excitations is captured and its vibration envelope recreated in 3D, using the methodology developed in this thesis. The approach is tested and used to identify changes in the model s vibration response, which in turn can be related to the presence of damage or any other structural modification. The approach is also demonstrated by recording the vibration envelope of larger case studies in 2D, which includes a full-scale bridge structure, confirming the relevance of the proposed measurement approach to real civil engineering case studies. This thesis then assesses the accuracy of the measurement approach in controlled motion tests. Considerations in the design of a survey using the LEMBI approach are discussed and limitations are described. The implications of the newly developed monitoring approach to structural testing are reviewed

Establishing the digital chain of evidence in biometric systems

Traditionally, a chain of evidence or chain of custody refers to the chronological documentation, or paper trail, showing the seizure, custody, control, transfer, analysis, and disposition of evidence, physical or electronic. Whether in the criminal justice system, military applications, or natural disasters, ensuring the accuracy and integrity of such chains is of paramount importance. Intentional or unintentional alteration, tampering, or fabrication of digital evidence can lead to undesirable effects. We find despite the consequences at stake, historically, no unique protocol or standardized procedure exists for establishing such chains. Current practices rely on traditional paper trails and handwritten signatures as the foundation of chains of evidence.;Copying, fabricating or deleting electronic data is easier than ever and establishing equivalent digital chains of evidence has become both necessary and desirable. We propose to consider a chain of digital evidence as a multi-component validation problem. It ensures the security of access control, confidentiality, integrity, and non-repudiation of origin. Our framework, includes techniques from cryptography, keystroke analysis, digital watermarking, and hardware source identification. The work offers contributions to many of the fields used in the formation of the framework. Related to biometric watermarking, we provide a means for watermarking iris images without significantly impacting biometric performance. Specific to hardware fingerprinting, we establish the ability to verify the source of an image captured by biometric sensing devices such as fingerprint sensors and iris cameras. Related to keystroke dynamics, we establish that user stimulus familiarity is a driver of classification performance. Finally, example applications of the framework are demonstrated with data collected in crime scene investigations, people screening activities at port of entries, naval maritime interdiction operations, and mass fatality incident disaster responses