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Machine Vision Inspection Systems, Machine Learning-Based Approaches

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2021-01-15

Total Pages: 352

ISBN-13: 1119786118

Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.

Machine Vision Inspection Systems, Machine Learning-Based Approaches

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2021-01-14

Total Pages: 354

ISBN-13: 111978610X

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Machine Vision Inspection Systems, Image Processing, Concepts, Methodologies, and Applications

Author: Muthukumaran Malarvel

Publisher: John Wiley & Sons

Published: 2020-06-30

Total Pages: 256

ISBN-13: 1119681804

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This edited book brings together leading researchers, academic scientists and research scholars to put forward and share their experiences and research results on all aspects of an inspection system for detection analysis for various machine vision applications. It also provides a premier interdisciplinary platform to present and discuss the most recent innovations, trends, methodology, applications, and concerns as well as practical challenges encountered and solutions adopted in the inspection system in terms of image processing and analytics of machine vision for real and industrial application. Machine vision inspection systems (MVIS) utilized all industrial and non-industrial applications where the execution of their utilities based on the acquisition and processing of images. MVIS can be applicable in industry, governmental, defense, aerospace, remote sensing, medical, and academic/education applications but constraints are different. MVIS entails acceptable accuracy, high reliability, high robustness, and low cost. Image processing is a well-defined transformation between human vision and image digitization, and their techniques are the foremost way to experiment in the MVIS. The digital image technique furnishes improved pictorial information by processing the image data through machine vision perception. Digital image processing has widely been used in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.,), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), barcode reading and traceability, medical diagnosis, weather forecasting, face recognition, defence and space research, etc. This edited book is designed to address various aspects of recent methodologies, concepts and research plan out to the readers for giving more depth insights for perusing research on machine vision using image processing techniques.

Machine Vision

Author: Jürgen Beyerer

Publisher: Springer

Published: 2015-10-01

Total Pages: 798

ISBN-13: 3662477947

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The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

Measurements and Instrumentation for Machine Vision

Author: Oleg Sergiyenko

Publisher: CRC Press

Published: 2024-06-26

Total Pages: 466

ISBN-13: 1040042988

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A comprehensive reference book that addresses the field of machine vision and its significance in cyber-physical systems. It explores the multidisciplinary nature of machine vision, involving electronic and mechatronic devices, artificial intelligence algorithms, embedded systems, control systems, robotics, interconnectivity, data science, and cloud computing. The book aims to provide advanced students, early career researchers, and established scholars with state-of-the-art knowledge and novel content related to the implementation of machine vision in engineering, scientific knowledge, and technological innovation. The chapters of the book delve into various topics and applications within the realm of machine vision. They cover areas such as camera and inertial measurement unit calibration, technical vision systems for human detection, design and evaluation of support systems using neural networks, UV sensing in contemporary applications, fiber Bragg grating arrays for medical diagnosis, color model creation for terrain recognition by robots, navigation systems for aircraft, object classification in infrared images, feature selection for vehicle/non-vehicle classification, visualization of sedimentation in extreme conditions, quality estimation of tea using machine vision, image dataset augmentation techniques, machine vision for astronomical images, agricultural automation, occlusion-aware disparity-based visual servoing, machine learning approaches for single-photon imaging, and augmented visual inertial wheel odometry. Each chapter is a result of expert research and collaboration, reviewed by peers and consulted by the book's editorial board. The authors provide in-depth reviews of the state of the art and present novel proposals, contributing to the development and futurist trends in the field of machine vision. "Measurements and Instrumentation for Machine Vision" serves as a valuable resource for researchers, students, and professionals seeking to explore and implement machine vision technologies in various domains, promoting sustainability, human-centered solutions, and global problem-solving.

Computer Vision and Recognition Systems

Author: Chiranji Lal Chowdhary

Publisher: CRC Press

Published: 2022-03-10

Total Pages: 272

ISBN-13: 1000400778

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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.

Machine Learning for Vision-Based Motion Analysis

Author: Liang Wang

Publisher: Springer Science & Business Media

Published: 2010-11-18

Total Pages: 377

ISBN-13: 0857290576

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Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets. Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.

Advanced Methods and Deep Learning in Computer Vision

Author: E. R. Davies

Publisher: Academic Press

Published: 2021-11-09

Total Pages: 584

ISBN-13: 0128221496

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Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field Illustrates principles with modern, real-world applications Suitable for self-learning or as a text for graduate courses

Visual Object Recognition

Author: Kristen Grauman

Publisher: Morgan & Claypool Publishers

Published: 2011

Total Pages: 184

ISBN-13: 1598299689

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The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: Specific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions

Computer Vision in Control Systems-2

Author: Margarita N. Favorskaya

Publisher: Springer

Published: 2014-10-30

Total Pages: 307

ISBN-13: 3319114301

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The research book is focused on the recent advances in computer vision methodologies and innovations in practice. The Contributions include: · Human Action Recognition: Contour-Based and Silhouette-based Approaches. · The Application of Machine Learning Techniques to Real Time Audience Analysis System. · Panorama Construction from Multi-view Cameras in Outdoor Scenes. · A New Real-Time Method of Contextual Image Description and Its Application in Robot Navigation and Intelligent Control. · Perception of Audio Visual Information for Mobile Robot Motion Control Systems. · Adaptive Surveillance Algorithms Based on the Situation Analysis. · Enhanced, Synthetic and Combined Vision Technologies for Civil Aviation. · Navigation of Autonomous Underwater Vehicles Using Acoustic and Visual Data Processing. · Efficient Denoising Algorithms for Intelligent Recognition Systems. · Image Segmentation Based on Two-dimensional Markov Chains. The book is directed to the PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.