Adaptive restoration of text images containing touching and broken characters

For document processing systems, automated data entry is generally performed by optical character recognition (OCR) systems. To make these systems practical, reliable OCR systems are essential. However, distortions in document images cause character recognition errors, thereby, reducing the accuracy of OCR systems. In document images, most OCR errors are caused by broken and touching characters. This thesis presents an adaptive system to restore text images distorted by touching and broken characters. The adaptive system uses the distorted text image and the output from an OCR system to generate the training character image. Using the training image and the distorted image, the system trains an adaptive restoration filter and then uses the trained filter to restore the distorted text image. To demonstrate the performance of this technique, it was applied to several distorted images containing touching or broken characters. The results show that this technique can improve both pixel and OCR accuracy of distorted text images containing touching or broken characters

Eye Detection and Face Recognition Across the Electromagnetic Spectrum

Biometrics, or the science of identifying individuals based on their physiological or behavioral traits, has increasingly been used to replace typical identifying markers such as passwords, PIN numbers, passports, etc. Different modalities, such as face, fingerprint, iris, gait, etc. can be used for this purpose. One of the most studied forms of biometrics is face recognition (FR). Due to a number of advantages over typical visible to visible FR, recent trends have been pushing the FR community to perform cross-spectral matching of visible images to face images from higher spectra in the electromagnetic spectrum.;In this work, the SWIR band of the EM spectrum is the primary focus. Four main contributions relating to automatic eye detection and cross-spectral FR are discussed. First, a novel eye localization algorithm for the purpose of geometrically normalizing a face across multiple SWIR bands for FR algorithms is introduced. Using a template based scheme and a novel summation range filter, an extensive experimental analysis show that this algorithm is fast, robust, and highly accurate when compared to other available eye detection methods. Also, the eye locations produced by this algorithm provides higher FR results than all other tested approaches. This algorithm is then augmented and updated to quickly and accurately detect eyes in more challenging unconstrained datasets, spanning the EM spectrum. Additionally, a novel cross-spectral matching algorithm is introduced that attempts to bridge the gap between the visible and SWIR spectra. By fusing multiple photometric normalization combinations, the proposed algorithm is not only more efficient than other visible-SWIR matching algorithms, but more accurate in multiple challenging datasets. Finally, a novel pre-processing algorithm is discussed that bridges the gap between document (passport) and live face images. It is shown that the pre-processing scheme proposed, using inpainting and denoising techniques, significantly increases the cross-document face recognition performance

Editing Shakespeare Violence, Text and Commodity in The Taming of the Shrew

Editing Shakespeare: Violence, Text, and Commodity in The Taming of the Shrew is an edition of one of Shakespeare’s earliest and most controversial comedies aimed at an undergraduate audience. Textually, The Taming of the Shrew is a complex and controversial play because two radically different versions of it have survived. My edition is written in the context of two other controversies, namely the function of scholarship in the humanities given Syracuse University’s commitment to scholarship in action and the abiding problem of domestic abuse. Though the printing industry is a driving force behind the production of new editions of Shakespearean texts, it is the social issue of domestic abuse that keeps The Taming of the Shrew at the forefront of classroom discussion. As we continue to debate the role of women in both early modern and contemporary domestic spheres, this text, a case study in domestic violence, provides an appropriate starting point and challenges our social response to literature that offers a representation of household abuse even within the frame of comedy. Historicizing Shakespeare’s play allows for a careful consideration of the texts and other cultural works that predate and accompany Shakespeare in the historical moment that saw the writing and production of this play. The most intense historical debate that underlies The Taming of the Shrew questions the relationship between Shakespeare’s play and a rival text titled The Taming of a Shrew. This textual debate questions authorship and authenticity as well as the nature of performance in and of the play itself. The critical debate centers itself in yet another controversy—the resolution of the play’s taming narrative. The focus of this resolution is Kate’s (in)famous final speech, and scholars have presented a variety of readings of these last lines. For decades, scholarship has asked, is Kate’s verbal expression of wifely obedience a true sign of her submission, or does she assert her authority by using the very structures of oppression to her own advantage? The Taming of the Shrew proves to be an elusive text. It demands focused and dedicated editorial labor and an historical yet modern frame of mind. The multitude of critical reflections, each with variant readings of the play’s gender dynamics, demonstrates that the play has maintained its presence in scholarly consciousness despite its status as a nearly four-hundred-year-old text. My edition works toward a uniquely comprehensive synthesis of contextual and critical materials and seeks to serve undergraduate students as an accessible and valuable version of this perennial play

Near-real-time TOMS, telecommunications and meteorological support for the 1987 Airborne Antarctic Ozone Experiment

The goal of the 1987 Airborne Antarctic Ozone Experiment was to improve the understanding of the mechanisms involved in the formation of the Antarctic ozone hole. Total ozone data taken by the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) played a central role in the successful outcome of the experiment. During the experiment, the near-real-time TOMS total ozone observations were supplied within hours of real time to the operations center in Punta Arenas, Chile. The final report summarizes the role which Research and Data Systems (RDS) Corporation played in the support of the experiment. The RDS provided telecommunications to support the science and operations efforts for the Airborne Antarctic Ozone Experiment, and supplied near real-time weather information to ensure flight and crew safety; designed and installed the telecommunications network to link NASA-GSFC, the United Kingdom Meteorological Office (UKMO), Palmer Station, the European Center for Medium-Range Weather Forecasts (ECMWF) to the operation at Punta Arenas; engineered and installed stations and other stand-alone systems to collect data from designated low-orbiting polar satellites and beacons; provided analyses of Nimbus-7 TOMS data and backup data products to Punta Arenas; and provided synoptic meteorological data analysis and reduction

Digital imaging technology assessment: Digital document storage project

An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes

Design and Real-World Application of Novel Machine Learning Techniques for Improving Face Recognition Algorithms

Recent progress in machine learning has made possible the development of real-world face recognition applications that can match face images as good as or better than humans. However, several challenges remain unsolved. In this PhD thesis, some of these challenges are studied and novel machine learning techniques to improve the performance of real-world face recognition applications are proposed. Current face recognition algorithms based on deep learning techniques are able to achieve outstanding accuracy when dealing with face images taken in unconstrained environments. However, training these algorithms is often costly due to the very large datasets and the high computational resources needed. On the other hand, traditional methods for face recognition are better suited when these requirements cannot be satisfied. This PhD thesis presents new techniques for both traditional and deep learning methods. In particular, a novel traditional face recognition method that combines texture and shape features together with subspace representation techniques is first presented. The proposed method is lightweight and can be trained quickly with small datasets. This method is used for matching face images scanned from identity documents against face images stored in the biometric chip of such documents. Next, two new techniques to increase the performance of face recognition methods based on convolutional neural networks are presented. Specifically, a novel training strategy that increases face recognition accuracy when dealing with face images presenting occlusions, and a new loss function that improves the performance of the triplet loss function are proposed. Finally, the problem of collecting large face datasets is considered, and a novel method based on generative adversarial networks to synthesize both face images of existing subjects in a dataset and face images of new subjects is proposed. The accuracy of existing face recognition algorithms can be increased by training with datasets augmented with the synthetic face images generated by the proposed method. In addition to the main contributions, this thesis provides a comprehensive literature review of face recognition methods and their evolution over the years. A significant amount of the work presented in this PhD thesis is the outcome of a 3-year-long research project partially funded by Innovate UK as part of a Knowledge Transfer Partnership between University of Hertfordshire and IDscan Biometrics Ltd (partnership number: 009547)