Digital hologram recording systems: some performance improvements

The work presented in this thesis was performed under the EU's Framework 7 (FP7) project, 'REAL3D'. The aim of this project is to develop methods based on digital holography for real time capture and display of 3D objects. This thesis forms a small subset of all the work done in this project. Much of the research work was aimed towards fullling our part of the requirements of the REAL3D project. The central theme of the research presented in this thesis is that of improving the performance of the digital holographic imaging system for its use in 3D display. This encompasses research into speed up of reconstruction algorithms, understanding the in uence of noise and developing techniques to increase resolution and angular perspective range in reconstructions. The main original contributions of this research work presented in this thesis are: A computer-interfaced automatic digital holographic imaging system employing `phase shifting' has been built. This system is capable of recording high-quality digital holograms of a real world 3D object. The object can be rotated on a rotational stage and a full 360 range of perspectives can be recorded. Speckle reduction using moving diusers can be performed to improve the image quality of the reconstructed images. A LabView based user friendly interface has been developed. Novel methods based on space-time tradeo and xed point arithmetic have been developed and implemented for speed- ing up the reconstruction algorithm used in digital holography. This has resulted in the publication of one peer-reviewed journal pub- lication and one conference proceeding [1, 2]. The in uence of additive noise, particularly quantization noise in digital holography has been studied in detail. A model has been developed to understand the in uence of noise on the re- constructed image quality. Based on this model, a method has been developed to suppress quantization noise in a memory ecient man- ner. This work led to the publication of two peer-reviewed journal publications [3, 4]. A novel method of removing the twin image has been devel- oped. Methods to increase the perspectives in holography based on synthetic aperture have been implemented. Apart from these primary contributions, the author of this thesis has also contributed in the form of assisting in experiments, creating gures for various papers, writing computer programs and discussions during group meetings. In total, 6 peer-reviewed journal papers (3 being primary author) have been published and 6 conference proceedings (3 being primary author) have been published. Additionally, 2 talks have been given at international conferences

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

On-board three-dimensional object tracking: Software and hardware solutions

We describe a real time system for recognition and tracking 3D objects such as UAVs, airplanes, fighters with the optical sensor. Given a 2D image, the system has to perform background subtraction, recognize relative rotation, scale and translation of the object to sustain a prescribed topology of the fleet. In the thesis a comparative study of different algorithms and performance evaluation is carried out based on time and accuracy constraints. For background subtraction task we evaluate frame differencing, approximate median filter, mixture of Gaussians and propose classification based on neural network methods. For object detection we analyze the performance of invariant moments, scale invariant feature transform and affine scale invariant feature transform methods. Various tracking algorithms such as mean shift with variable and a fixed sized windows, scale invariant feature transform, Harris and fast full search based on fast fourier transform algorithms are evaluated. We develop an algorithm for the relative rotations and the scale change calculation based on Zernike moments. Based on the design criteria the selection is made for on-board implementation. The candidate techniques have been implemented on the Texas Instrument TMS320DM642 EVM board. It is shown in the thesis that 14 frames per second can be processed; that supports the real time implementation of the tracking system under reasonable accuracy limits

A new technique for video copy-move forgery detection

This thesis describes an algorithm for detecting copy-move falsifications in digital video. The thesis is composed of 5 chapters. In the first chapter there is an introduction to forgery detection for digital images and videos. Chapters 2, 3 and 4 describe in detail the techniques used for the implementation of the detection algorithm. The experimental results are presented in the fifth and last chapter

Vision Based Extraction of Nutrition Information from Skewed Nutrition Labels

An important component of a healthy diet is the comprehension and retention of nutritional information and understanding of how different food items and nutritional constituents affect our bodies. In the U.S. and many other countries, nutritional information is primarily conveyed to consumers through nutrition labels (NLs) which can be found in all packaged food products. However, sometimes it becomes really challenging to utilize all this information available in these NLs even for consumers who are health conscious as they might not be familiar with nutritional terms or find it difficult to integrate nutritional data collection into their daily activities due to lack of time, motivation, or training. So it is essential to automate this data collection and interpretation process by integrating Computer Vision based algorithms to extract nutritional information from NLs because it improves the user’s ability to engage in continuous nutritional data collection and analysis. To make nutritional data collection more manageable and enjoyable for the users, we present a Proactive NUTrition Management System (PNUTS). PNUTS seeks to shift current research and clinical practices in nutrition management toward persuasion, automated nutritional information processing, and context-sensitive nutrition decision support. PNUTS consists of two modules, firstly a barcode scanning module which runs on smart phones and is capable of vision-based localization of One Dimensional (1D) Universal Product Code (UPC) and International Article Number (EAN) barcodes with relaxed pitch, roll, and yaw camera alignment constraints. The algorithm localizes barcodes in images by computing Dominant Orientations of Gradients (DOGs) of image segments and grouping smaller segments with similar DOGs into larger connected components. Connected components that pass given morphological criteria are marked as potential barcodes. The algorithm is implemented in a distributed, cloud-based system. The system’s front end is a smartphone application that runs on Android smartphones with Android 4.2 or higher. The system’s back end is deployed on a five node Linux cluster where images are processed. The algorithm was evaluated on a corpus of 7,545 images extracted from 506 videos of bags, bottles, boxes, and cans in a supermarket. The DOG algorithm was coupled to our in-place scanner for 1D UPC and EAN barcodes. The scanner receives from the DOG algorithm the rectangular planar dimensions of a connected component and the component’s dominant gradient orientation angle referred to as the skew angle. The scanner draws several scan lines at that skew angle within the component to recognize the barcode in place without any rotations. The scanner coupled to the localizer was tested on the same corpus of 7,545 images. Laboratory experiments indicate that the system can localize and scan barcodes of any orientation in the yaw plane, of up to 73.28 degrees in the pitch plane, and of up to 55.5 degrees in the roll plane. The videos have been made public for all interested research communities to replicate our findings or to use them in their own research. The front end Android application is available for free download at Google Play under the title of NutriGlass. This module is also coupled to a comprehensive NL database from which nutritional information can be retrieved on demand. Currently our NL database consists of more than 230,000 products. The second module of PNUTS is an algorithm whose objective is to determine the text skew angle of an NL image without constraining the angle’s magnitude. The horizontal, vertical, and diagonal matrices of the (Two Dimensional) 2D Haar Wavelet Transform are used to identify 2D points with significant intensity changes. The set of points is bounded with a minimum area rectangle whose rotation angle is the text’s skew. The algorithm’s performance is compared with the performance of five text skew detection algorithms on 1001 U.S. nutrition label images and 2200 single- and multi-column document images in multiple languages. To ensure the reproducibility of the reported results, the source code of the algorithm and the image data have been made publicly available. If the skew angle is estimated correctly, optical character recognition (OCR) techniques can be used to extract nutrition information

Vector synthesis: a media archaeological investigation into sound-modulated light

Vector Synthesis is a computational art project inspired by theories of media archaeology, by the history of computer and video art, and by the use of discarded and obsolete technologies such as the Cathode Ray Tube monitor. This text explores the military and techno-scientific legacies at the birth of modern computing, and charts attempts by artists of the subsequent two decades to decouple these tools from their destructive origins. Using this history as a basis, the author then describes a media archaeological, real time performance system using audio synthesis and vector graphics display techniques to investigate direct, synesthetic relationships between sound and image. Key to this system, realized in the Pure Data programming environment, is a didactic, open source approach which encourages reuse and modification by other artists within the experimental audiovisual arts community.Holzer, Dere