Arbitrary Keyword Spotting in Handwritten Documents

Despite the existence of electronic media in today’s world, a considerable amount of written communications is in paper form such as books, bank cheques, contracts, etc. There is an increasing demand for the automation of information extraction, classification, search, and retrieval of documents. The goal of this research is to develop a complete methodology for the spotting of arbitrary keywords in handwritten document images. We propose a top-down approach to the spotting of keywords in document images. Our approach is composed of two major steps: segmentation and decision. In the former, we generate the word hypotheses. In the latter, we decide whether a generated word hypothesis is a specific keyword or not. We carry out the decision step through a two-level classification where first, we assign an input image to a keyword or non-keyword class; and then transcribe the image if it is passed as a keyword. By reducing the problem from the image domain to the text domain, we do not only address the search problem in handwritten documents, but also the classification and retrieval, without the need for the transcription of the whole document image. The main contribution of this thesis is the development of a generalized minimum edit distance for handwritten words, and to prove that this distance is equivalent to an Ergodic Hidden Markov Model (EHMM). To the best of our knowledge, this work is the first to present an exact 2D model for the temporal information in handwriting while satisfying practical constraints. Some other contributions of this research include: 1) removal of page margins based on corner detection in projection profiles; 2) removal of noise patterns in handwritten images using expectation maximization and fuzzy inference systems; 3) extraction of text lines based on fast Fourier-based steerable filtering; 4) segmentation of characters based on skeletal graphs; and 5) merging of broken characters based on graph partitioning. Our experiments with a benchmark database of handwritten English documents and a real-world collection of handwritten French documents indicate that, even without any word/document-level training, our results are comparable with two state-of-the-art word spotting systems for English and French documents

Adaptive Methods for Robust Document Image Understanding

A vast amount of digital document material is continuously being produced as part of major digitization efforts around the world. In this context, generic and efficient automatic solutions for document image understanding represent a stringent necessity. We propose a generic framework for document image understanding systems, usable for practically any document types available in digital form. Following the introduced workflow, we shift our attention to each of the following processing stages in turn: quality assurance, image enhancement, color reduction and binarization, skew and orientation detection, page segmentation and logical layout analysis. We review the state of the art in each area, identify current defficiencies, point out promising directions and give specific guidelines for future investigation. We address some of the identified issues by means of novel algorithmic solutions putting special focus on generality, computational efficiency and the exploitation of all available sources of information. More specifically, we introduce the following original methods: a fully automatic detection of color reference targets in digitized material, accurate foreground extraction from color historical documents, font enhancement for hot metal typesetted prints, a theoretically optimal solution for the document binarization problem from both computational complexity- and threshold selection point of view, a layout-independent skew and orientation detection, a robust and versatile page segmentation method, a semi-automatic front page detection algorithm and a complete framework for article segmentation in periodical publications. The proposed methods are experimentally evaluated on large datasets consisting of real-life heterogeneous document scans. The obtained results show that a document understanding system combining these modules is able to robustly process a wide variety of documents with good overall accuracy

Document image restoration - For document images scanned from bound volumes -

Ph.DDOCTOR OF PHILOSOPH

Techniques for document image processing in compressed domain

The main objective for image compression is usually considered the minimization of storage space. However, as the need to frequently access images increases, it is becoming more important for people to process the compressed representation directly. In this work, the techniques that can be applied directly and efficiently to digital information encoded by a given compression algorithm are investigated. Lossless compression schemes and information processing algorithms for binary document images and text data are two closely related areas bridged together by the fast processing of coded data. The compressed domains, which have been addressed in this work, i.e., the ITU fax standards and JBIG standard, are two major schemes used for document compression. Based on ITU Group IV, a modified coding scheme, MG4, which explores the 2-dimensional correlation between scan lines, is developed. From the viewpoints of compression efficiency and processing flexibility of image operations, the MG4 coding principle and its feature-preserving behavior in the compressed domain are investigated and examined. Two popular coding schemes in the area of bi-level image compression, run-length and Group IV, are studied and compared with MG4 in the three aspects of compression complexity, compression ratio, and feasibility of compressed-domain algorithms. In particular, for the operations of connected component extraction, skew detection, and rotation, MG4 shows a significant speed advantage over conventional algorithms. Some useful techniques for processing the JBIG encoded images directly in the compressed domain, or concurrently while they are being decoded, are proposed and generalized; In the second part of this work, the possibility of facilitating image processing in the wavelet transform domain is investigated. The textured images can be distinguished from each other by examining their wavelet transforms. The basic idea is that highly textured regions can be segmented using feature vectors extracted from high frequency bands based on the observation that textured images have large energies in both high and middle frequencies while images in which the grey level varies smoothly are heavily dominated by the low-frequency channels in the wavelet transform domain. As a result, a new method is developed and implemented to detect textures and abnormalities existing in document images by using polynomial wavelets. Segmentation experiments indicate that this approach is superior to other traditional methods in terms of memory space and processing time

Real-Time Multi-Fisheye Camera Self-Localization and Egomotion Estimation in Complex Indoor Environments

In this work a real-time capable multi-fisheye camera self-localization and egomotion estimation framework is developed. The thesis covers all aspects ranging from omnidirectional camera calibration to the development of a complete multi-fisheye camera SLAM system based on a generic multi-camera bundle adjustment method

Airborne thermography and ground geophysical investigation for detecting shallow ground disturbance under vegetation

This thesis discusses the potential of airborne thermal prospection for detecting shallow ground disturbance beneath vegetation based on images acquired by the NERC Airborne Thematic Mapper (ATM) at thermal infrared wavelengths. Shallow ground disturbance creates a differential heat flux due to a variation in the thermal properties between disturbed and undisturbed soils. When observed above a canopy, the effect of vegetation growth on the thermal regime of the underlying soils is poorly understood. The research extends current understanding by examining areas where ground disturbance is known to exist under variable vegetation cover at an archaeological site at Bosworth, Leicestershire and areas of abandoned mine activity on Baildon Moor, W. Yorkshire and in the N. Pennine Orefield, Weardale. The investigation focuses on qualitative image interpretation techniques, where anomalies on day and night thermal images are compared with those manifest on the multispectral images, and a more quantitative approach of Apparent Thermal Inertia (ATI) modelling. Physical thermal inertia is a parameter that is sensitive to volumetric variations in the soil, but cannot be measured directly using remote sensing techniques. However, an apparent thermal inertia is determined by examining the day and night temperature contrast of the surface, where spatial variations can signify potential features buried in the near-surface environment. Ground temperature profiling at the Bosworth site indicates that diurnal heat dissipates between 0.20-0.50m at an early stage in vegetation development with progressively lower diurnal amplitudes observed at 0.20m as the vegetation develops. Results also show that the time of diurnal maximum temperature occurs progressively later as vegetation develops, implying an importance for thermal image acquisition. The quantitative investigation concentrates on the Bosworth site where extensive ground geophysical prospection was performed and vertical soil samples extracted across features of variable multispectral, thermal and ATI response to enable comparison of the observed airborne thermal response with physical soil properties. Results suggest that there is a high correlation between ATI and soil moisture properties at 0.15-0.25m depth (R(^2)=0.99) at an early stage in cereal crop development but has a high correlation at a wider depth range (0.10-0.30m) at a later stage in development (R(^2)=0.98). The high correlation between physical ground disturbance and the thermal response is also corroborated qualitatively with the results of the resistivity surveys. The ATI modelling reveals similar features to those evident on day or night thermal images at an early stage in vegetation growth, suggesting that thermal imaging during the day at an early stage in vegetation growth may supply sufficient information on features buried in the near-surface environment. Airborne thermal imaging therefore provides a useful complementary prospection tool for archaeological and geological applications for surfaces covered by vegetation

Design/cost tradeoff studies. Appendix A. Supporting analyses and tradeoffs, book 2. Earth Observatory Satellite system definition study (EOS)

Attitude reference systems for use with the Earth Observatory Satellite (EOS) are described. The systems considered are fixed and gimbaled star trackers, star mappers, and digital sun sensors. Covariance analyses were performed to determine performance for the most promising candidate in low altitude and synchronous orbits. The performance of attitude estimators that employ gyroscopes which are periodically updated by a star sensor is established by a single axis covariance analysis. The other systems considered are: (1) the propulsion system design, (2) electric power and electrical integration, (3) thermal control, (4) ground data processing, and (5) the test plan and cost reduction aspects of observatory integration and test

Eighth International Workshop on Laser Ranging Instrumentation

The Eighth International Workshop for Laser Ranging Instrumentation was held in Annapolis, Maryland in May 1992, and was sponsored by the NASA Goddard Space Flight Center in Greenbelt, Maryland. The workshop is held once every 2 to 3 years under differing institutional sponsorship and provides a forum for participants to exchange information on the latest developments in satellite and lunar laser ranging hardware, software, science applications, and data analysis techniques. The satellite laser ranging (SLR) technique provides sub-centimeter precision range measurements to artificial satellites and the Moon. The data has application to a wide range of Earth and lunar science issues including precise orbit determination, terrestrial reference frames, geodesy, geodynamics, oceanography, time transfer, lunar dynamics, gravity and relativity

Attitude Determination & Control System Design and Implementation for a 6U CubeSat Proximity Operations Mission

The purpose of this work is to discuss the attitude determination and control system (ADCS) design process and implementation for a 12 kg, 6U (36.6 cm x 23.9 cm x 27.97 cm) CubeSat class nano-satellite. The design is based on the requirements and capabilities of the Application for Resident Space Object Proximity Analysis and IMAging (ARAPAIMA) proximity operations mission. The satellite is equipped with a cold gas propulsion system capable of exerting 2.5 mN m torques in both directions about each body axis. The attitude sensors include an angular rate gyro and star tracker (STR), supplemented by the payload optical array cameras. The dynamic simulation of the satellite includes extensive environmental models and analyses that show how the satellite attitude is affected by aerodynamic drag, solar radiation pressure, gravity gradient torques, and residual magnetic moments. A mechanical propellant slosh model and a reaction torque analysis of the deployable solar panel hinges approximate the internal dynamics of the satellite. A trade study is presented to justify the use of a reaction control thruster actuated system over the more traditional reaction wheel configuration. Both actuation systems are modeled to hardware specifications and their propellant and energy requirements are examined alongside pointing performance. Two methods of accounting for sensor noise and sampling rates are presented. The first is an extended Kalman filter based on the nonlinear model of a rate gyro coupled with quaternion attitude kinematics. The second presents a gyro-less angular rate observer capable of extrapolating STR measurements to the desired frequency. An additional method uses images from the payload cameras to perform [camera] frame centering maneuvers and to address the possibility of bias in the controller reference signal. Four different controllers are described to reflect the chronological progression of the ADCS design. The first controller, designed to perform long angle maneuvers and target tracking, utilizes fixed gain eigenaxis control. The same controller is then augmented with a parallel proportional-integral-derivative (PID) type control law using scheduled gains. This configuration is designed to switch between eigenaxis and PID control during imaging procedures to take advantage of the integral control introduced by the PID algorithm. To reduce system complexity, a modified eigenaxis control law, which incorporates scheduled integral control but does not require a switch to PID control, is introduced. A discrete time equivalent of the modified eigenaxis control law is also developed. Additionally, a brief description of a detumbling control law is presented. Each of the four control laws is paired and tested with the different feedback and estimation methods discussed. An extensive showcase of numerical simulation results outlines the pointing performance of each system configuration and evaluates their capabilities of meeting a 1 arcmin pointing requirement. A comparison of the different properties and performance of each control system configuration precedes the selection of the discrete modified eigenaxis control law as the best alternative

Chemometric tools for automated method-development and data interpretation in liquid chromatography

The thesis explores the challenges and advancements in the field of liquid chromatography (LC), particularly focusing on complex sample analysis using high-resolution mass spectrometry (MS) and two-dimensional (2D) LC techniques. The research addresses the need for efficient optimization and data-handling strategies in modern LC practice. The thesis is divided into several chapters, each addressing specific aspects of LC and polymer analysis. Chapter 2 provides an overview of the need for chemometric tools in LC practice, discussing methods for processing and analyzing data from 1D and 2D-LC systems and how chemometrics can be utilized for method development and optimization. Chapter 3 introduces a novel approach for interpreting the molecular-weight distribution and intrinsic viscosity of polymers, allowing quantitative analysis of polymer properties without prior knowledge of their interactions. This method correlates the curvature parameter of the Mark-Houwink plot with the polymer's structural and chemical properties. Chapters 4 and 5 focus on the analysis of cellulose ethers (CEs), essential in various industrial applications. A new method is presented for mapping the substitution degree and composition of CE samples, providing detailed compositional distributions. Another method involves a comprehensive 2D LC-MS/MS approach for analyzing hydroxypropyl methyl cellulose (HPMC) monomers, revealing subtle differences in composition between industrial HPMC samples. Chapter 6 introduces AutoLC, an algorithm for automated and interpretive development of 1D-LC separations. It uses retention modeling and Bayesian optimization to achieve optimal separation within a few iterations, significantly improving the efficiency of gradient LC separations. Chapter 7 focuses on the development of an open-source algorithm for automated method development in 2D-LC-MS systems. This algorithm improves separation performance by refining gradient profiles and accurately predicting peak widths, enhancing the reliability of complex gradient LC separations. Chapter 8 addresses the challenge of gradient deformation in LC instruments. An algorithm based on the stable function corrects instrument-specific gradient deformations, enabling accurate determination of analyte retention parameters and improving data comparability between different sources. Chapter 9 introduces a novel approach using capacitively-coupled-contactless-conductivity detection (C4D) to measure gradient profiles without adding tracer components. This method enhances inter-system transferability of retention models for polymers, overcoming the limitations of UV-absorbance detectable tracer components. Chapter 10 discusses practical choices and challenges faced in the thesis chapters, highlighting the need for well-defined standard samples in industrial polymer analysis and emphasizing the importance of generalized problem-solving approaches. The thesis identifies future research directions, emphasizing the importance of computational-assisted methods for polymer analysis, the utilization of online reaction modulation techniques, and exploring continuous distributions obtained through size-exclusion chromatography (SEC) in conjunction with triple detection. Chemometric tools are recognized as essential for gaining deeper insights into polymer chemistry and improving data interpretation in the field of LC