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Interactive Image Processing for Machine Vision

Interactive Image Processing for Machine Vision
Author: Bruce G. Batchelor
Publisher: Springer
Total Pages: 394
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1447103939

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Machine vision systems offer great potential in a large number of areas of manufacturing industry and are used principally for Automated Visual Inspection and Robot Vision. This publication presents the state of the art in image processing. It discusses techniques which have been developed for designing machines for use in industrial inspection and robot control, putting the emphasis on software and algorithms. A comprehensive set of image processing subroutines, which together form the basic vocabulary for the versatile image processing language IIPL, is presented. This language has proved to be extremely effective, working as a design tool, in solving numerous practical inspection problems. The merging of this language with Prolog provides an even more powerful facility which retains the benefits of human and machine intelligence. The authors bring together the practical experience and the picture material from a leading industrial research laboratory and the mathematical foundations necessary to understand and apply concepts in image processing. Interactive Image Processing is a self-contained reference book that can also be used in graduate level courses in electrical engineering, computer science and physics.


Real-Time Medical Image Processing

Real-Time Medical Image Processing
Author: Morio Onoe
Publisher: Springer Science & Business Media
Total Pages: 260
Release: 2012-12-06
Genre: Computers
ISBN: 1475701217

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In order to rea1ize real-time medica1 imaging systems, such as are used for computed tomography, automated miscroscopy, dynamic radioisotope imaging, etc., special techno1ogy is required. The high-speed image sour ce must be successfu11y married with the u1tra high-speed computer. Usua11y the ordinary genera1-purpose computer is found to be inadequate to the image generation and/or image pro cessing task. The ordinary computer executes instructions at be tween 1 and 10 million per second. Speed has improved by only about a factor of 10 during the past 20 years. In contrast a typical com puter used in recognizing blood cell images at 10,000 per hour must execute instructions at between 1 billion and 10 billion per second. Simi1ar execution rates are required to construct a computed tomogra phy image in real-time (1 to 10 seconds). For the reasons given above, engineering development in image generation and processing in the field of biomedicine has become a discipline unto itself; a discipline wherein the computer engineer is driven to design extremely high-speed machines that far surpass the ordinary computer and the x-ray, radioisotope, or microscope scanner designer must also produce equipment whose specifications extend far beyond the state-of-the-art."


Intelligent Image Processing in Prolog

Intelligent Image Processing in Prolog
Author: Bruce G. Batchelor
Publisher: Springer Science & Business Media
Total Pages: 383
Release: 2012-12-06
Genre: Computers
ISBN: 1447104013

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After a slow and somewhat tentative beginning, machine vision systems are now finding widespread use in industry. So far, there have been four clearly discernible phases in their development, based upon the types of images processed and how that processing is performed: (1) Binary (two level) images, processing in software (2) Grey-scale images, processing in software (3) Binary or grey-scale images processed in fast, special-purpose hardware (4) Coloured/multi-spectral images Third-generation vision systems are now commonplace, although a large number of binary and software-based grey-scale processing systems are still being sold. At the moment, colour image processing is commercially much less significant than the other three and this situation may well remain for some time, since many industrial artifacts are nearly monochrome and the use of colour increases the cost of the equipment significantly. A great deal of colour image processing is a straightforward extension of standard grey-scale methods. Industrial applications of machine vision systems can also be sub divided, this time into two main areas, which have largely retained distinct identities: (i) Automated Visual Inspection (A VI) (ii) Robot Vision (RV) This book is about a fifth generation of industrial vision systems, in which this distinction, based on applications, is blurred and the processing is marked by being much smarter (i. e. more "intelligent") than in the other four generations.


Image Processing for Engineers

Image Processing for Engineers
Author: Fawwaz Tayssir Ulaby
Publisher:
Total Pages: 438
Release: 2018-03-30
Genre: Image processing
ISBN: 9781607854883

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"Designed for a course on image processing (IP) aimed at both graduate students as well as undergraduates in their senior year, in any field of engineering, this book starts with an overview in Chapter 1 of how imaging sensors--from cameras to radars to MRIs and CAT--form images, and then proceeds to cover a wide array of image processing topics. The IP topics include: image interpolation, magnification, thumbnails, and sharpening, edge detection, noise filtering, de-blurring of blurred images, supervised and unsupervised learning, and image segmentation, among many others. As a prelude to the chapters focused on image processing (Chapters 3-12), the book offers in Chapter 2 a review of 1-D signals and systems, borrowed from our 2018 book Signals and Systems: Theory and Applications, by Ulaby and Yagle."--Preface.


Markov Random Fields for Vision and Image Processing

Markov Random Fields for Vision and Image Processing
Author: Andrew Blake
Publisher: MIT Press
Total Pages: 472
Release: 2011-07-22
Genre: Computers
ISBN: 0262015773

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State-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study. This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications. After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools.