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Computer-readable documents have become ubiquitous in everyday life - from legacy documents that have been digitized, to new documents that have been created electronically. As the number of electronic documents continues to grow, so does the importance of digital methods for processing and managing these documents. This comprehensive text/reference provides a broad review of the issues involved in handling and processing digital documents. Examining the full range of a document's lifetime, the book covers acquisition, representation, security, pre-processing, layout analysis, understanding, analysis of single components, information extraction, filing, indexing and retrieval. A background knowledge of the area is not required, beyond familiarity with basic concepts of computer science and mathematics; deeper technical content is provided in discrete subsections that are not essential for an understanding of other parts of the book. Topics and features: With a Foreword by Professor George Nagy of Rensselaer Polytechnic Institute, New York, USA Provides a list of acronyms and a glossary of technical terms Contains appendices covering key concepts in machine learning, and providing a case study on building an intelligent system for digital document and library management Discusses issues of security, and legal aspects of digital documents Examines core issues of document image analysis, and image processing techniques of particular relevance to digitized documents Reviews the resources available for natural language processing, in addition to techniques of linguistic analysis for content handling Investigates methods for extracting and retrieving data/information from a document, including representation at a semantic level Undergraduate and graduate students will find the text a valuable general reference on the subject, and researchers will discover how their specific area of interest is interrelated with other disciplines involved in digital document processing. The book also supplies a repertoire of potential technological solutions for professionals working on digital documents. Dr. Stefano Ferilli is an associate professor at the University of Bari, Italy, where he is Director of the Interdepartmental Center for Logic and Applications.

Computer. Automation --- beeldverwerking

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This work presents a full generic approach to the detection and recognition of traffic signs. The approach, originally developed for a mobile mapping application, is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization - Error-Correcting Output Codes - and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future lines of research, and continuing challenges for traffic sign recognition.

Computer. Automation --- beeldverwerking

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Our knowledge of the surrounding world is obtained by our senses, of which vision is the most important for the information it can provide. In artificial systems, the field of Computer Vision aims to identify physical objects and scenes from captured images, to make useful decisions. This involves the processing and analysis of images, video data, and multi-dimensional data like medical scans. In this context, motion provides a stimulus for detecting objects in movement within the observed scene. Moreover, motion allows other characteristics to be obtained, such as object shape, speed or trajectory, which are meaningful for detection and recognition. However, the motion observable in a visual input can be due to different factors: movement of the imaged objects, movement of the observer, motion of the light sources, or a combination of these. This work focuses on motion detection from images captured by perspective and fisheye still cameras, proposing a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images is studied, allowing a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement against a dynamic background. This permits the development of a surveillance mechanism that removes the constraint of observing a scene free of foreground elements to obtain a reliable background model, since this situation cannot be guaranteed when operating in an unknown environment. Other problems are also addressed for the successful handling of changes in illumination, the distinction between foreground and background elements, and non-uniform vacillating backgrounds.

Computer. Automation --- beeldverwerking

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Image segmentation consists of dividing an image domain into disjoint regions according to a characterization of the image within or in-between the regions. Therefore, segmenting an image is to divide its domain into relevant components. The efficient solution of the key problems in image segmentation promises to enable a rich array of useful applications. The current major application areas include robotics, medical image analysis, remote sensing, scene understanding, and image database retrieval. The subject of this book is image segmentation by variational methods with a focus on formulations which use closed regular plane curves to define the segmentation regions and on a level set implementation of the corresponding active curve evolution algorithms. Each method is developed from an objective functional which embeds constraints on both the image domain partition of the segmentation and the image data within or in-between the partition regions. The necessary conditions to optimize the objective functional are then derived and solved numerically. The book covers, within the active curve and level set formalism, the basic two-region segmentation methods, multiregion extensions, region merging, image modeling, and motion based segmentation. To treat various important classes of images, modeling investigates several parametric distributions such as the Gaussian, Gamma, Weibull, and Wishart. It also investigates non-parametric models. In motion segmentation, both optical flow and the movement of real three-dimensional objects are studied.

Computer. Automation --- beeldverwerking --- signaalverwerking

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This book systematically addresses the quantification of quality aspects of multimodal interactive systems. The conceptual structure is based on a schematic view on human-computer interaction where the user interacts with the system and perceives it via input and output interfaces. Thus, aspects of multimodal interaction are analyzed first, followed by a discussion of the evaluation of output and input and concluding with a view on the evaluation of a complete system.

Computer. Automation --- beeldverwerking --- informatica --- signaalverwerking