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Author: Pradip K. Sinha
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819482020
Category : Computer vision
Languages : en
Pages : 0
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Book Description
Machine vision comprises three integrated processes: acquisition, preprocessing, and image analysis. While many resources discuss application-specific image analysis, there has been no unified account of image acquisition hardware and preprocessing - until now. This is a comprehensive, exhaustive reference text detailing every aspect of acquisition and preprocessing, from the illumination of a scene to the optics of image forming, from CCD and CMOS image capture to the transformation of the captured image.
Author: Pradip K. Sinha
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819482020
Category : Computer vision
Languages : en
Pages : 0
Get Book Here
Book Description
Machine vision comprises three integrated processes: acquisition, preprocessing, and image analysis. While many resources discuss application-specific image analysis, there has been no unified account of image acquisition hardware and preprocessing - until now. This is a comprehensive, exhaustive reference text detailing every aspect of acquisition and preprocessing, from the illumination of a scene to the optics of image forming, from CCD and CMOS image capture to the transformation of the captured image.
Author: Anil Anthony Bharath
Publisher: Artech House
ISBN: 1596932252
Category : Computers
Languages : en
Pages : 453
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Book Description
This interdisciplinary work brings you to the cutting edge of emerging technologies inspired by human sight, ranging from semiconductor photoreceptors based on novel organic polymers and retinomorphic processing circuitry to low-powered devices that replicate spatial and temporal processing in the brain. Moreover, it is the first work of its kind that integrates the full range of physiological, engineering, and mathematical issues and advances together in a single source.
Author: Mohamed Elgendy
Publisher: Manning
ISBN: 1617296198
Category : Computers
Languages : en
Pages : 478
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Book Description
How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings
Author: Domingo Mery
Publisher: Springer Nature
ISBN: 3030567699
Category : Computers
Languages : en
Pages : 473
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Book Description
[FIRST EDITION] This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Features: introduces the mathematical background for monocular and multiple view geometry; describes the main techniques for image processing used in X-ray testing; presents a range of different representations for X-ray images, explaining how these enable new features to be extracted from the original image; examines a range of known X-ray image classifiers and classification strategies; discusses some basic concepts for the simulation of X-ray images and presents simple geometric and imaging models that can be used in the simulation; reviews a variety of applications for X-ray testing, from industrial inspection and baggage screening to the quality control of natural products; provides supporting material at an associated website, including a database of X-ray images and a Matlab toolbox for use with the book’s many examples.
Author: Andreas Maier
Publisher: Springer
ISBN: 3319965204
Category : Computers
Languages : en
Pages : 263
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Book Description
This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.
Author: Bruce G. Batchelor
Publisher: Springer Science & Business Media
ISBN: 1447104315
Category : Computers
Languages : en
Pages : 475
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Book Description
The application of intelligent imaging techniques to industrial vision problems is an evolving aspect of current machine vision research. Machine vision is a relatively new technology, more concerned with systems engineering than with computer science, and with much to offer the manufacturing industry in terms of improving efficiency, safety and product quality. Beginning with an introductory chapter on the basic concepts, the authors develop these ideas to describe intelligent imaging techniques for use in a new generation of industrial imaging systems. Sections cover the application of AI languages such as Prolog, the use of multi-media interfaces and multi-processor systems, external device control, and colour recognition. The text concludes with a discussion of several case studies that illustrate how intelligent machine vision techniques can be used in industrial applications.
Author: Sarfraz, Muhammad
Publisher: IGI Global
ISBN: 1466660317
Category : Computers
Languages : en
Pages : 391
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Book Description
The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies features timely and informative research on the design and development of computer vision and image processing applications in intelligent agents as well as in multimedia technologies. Covering a diverse set of research in these areas, this publication is ideally designed for use by academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.
Author: Chiranji Lal Chowdhary
Publisher: CRC Press
ISBN: 1000400778
Category : Computers
Languages : en
Pages : 273
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Book Description
This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.
Author: Margarita N. Favorskaya
Publisher: Springer
ISBN: 3319106538
Category : Technology & Engineering
Languages : en
Pages : 385
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Book Description
This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: · Morphological Image Analysis for Computer Vision Applications. · Methods for Detecting of Structural Changes in Computer Vision Systems. · Hierarchical Adaptive KL-based Transform: Algorithms and Applications. · Automatic Estimation for Parameters of Image Projective Transforms Based on Object-invariant Cores. · A Way of Energy Analysis for Image and Video Sequence Processing. · Optimal Measurement of Visual Motion Across Spatial and Temporal Scales. · Scene Analysis Using Morphological Mathematics and Fuzzy Logic. · Digital Video Stabilization in Static and Dynamic Scenes. · Implementation of Hadamard Matrices for Image Processing. · A Generalized Criterion of Efficiency for Telecommunication Systems. The book is directed to PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.
Author: Bart M. Haar Romeny
Publisher: Springer Science & Business Media
ISBN: 140208840X
Category : Computers
Languages : en
Pages : 470
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Book Description
Many approaches have been proposed to solve the problem of finding the optic flow field of an image sequence. Three major classes of optic flow computation techniques can discriminated (see for a good overview Beauchemin and Barron IBeauchemin19951): gradient based (or differential) methods; phase based (or frequency domain) methods; correlation based (or area) methods; feature point (or sparse data) tracking methods; In this chapter we compute the optic flow as a dense optic flow field with a multi scale differential method. The method, originally proposed by Florack and Nielsen [Florack1998a] is known as the Multiscale Optic Flow Constrain Equation (MOFCE). This is a scale space version of the well known computer vision implementation of the optic flow constraint equation, as originally proposed by Horn and Schunck [Horn1981]. This scale space variation, as usual, consists of the introduction of the aperture of the observation in the process. The application to stereo has been described by Maas et al. [Maas 1995a, Maas 1996a]. Of course, difficulties arise when structure emerges or disappears, such as with occlusion, cloud formation etc. Then knowledge is needed about the processes and objects involved. In this chapter we focus on the scale space approach to the local measurement of optic flow, as we may expect the visual front end to do. 17. 2 Motion detection with pairs of receptive fields As a biologically motivated start, we begin with discussing some neurophysiological findings in the visual system with respect to motion detection.
