Practical Guide to Machine Vision Software

An Introduction with LabVIEW

Author: Kye-Si Kwon,Steven Ready

Publisher: John Wiley & Sons

ISBN: 3527337563

Category: Computers

Page: 296

View: 3751

For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.

Practical Guide to Machine Vision Software

An Introduction with LabVIEW

Author: Kye-Si Kwon,Steven Ready

Publisher: John Wiley & Sons

ISBN: 3527684115

Category: Computers

Page: 296

View: 8288

For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.

Handbook of Machine and Computer Vision

The Guide for Developers and Users

Author: Alexander Hornberg

Publisher: John Wiley & Sons

ISBN: 352741343X

Category: Computers

Page: 848

View: 4489

The second edition of this accepted reference work has been updated to reflect the rapid developments in the field and now covers both 2D and 3D imaging. Written by expert practitioners from leading companies operating in machine vision, this one-stop handbook guides readers through all aspects of image acquisition and image processing, including optics, electronics and software. The authors approach the subject in terms of industrial applications, elucidating such topics as illumination and camera calibration. Initial chapters concentrate on the latest hardware aspects, ranging from lenses and camera systems to camera-computer interfaces, with the software necessary discussed to an equal depth in later sections. These include digital image basics as well as image analysis and image processing. The book concludes with extended coverage of industrial applications in optics and electronics, backed by case studies and design strategies for the conception of complete machine vision systems. As a result, readers are not only able to understand the latest systems, but also to plan and evaluate this technology. With more than 500 images and tables to illustrate relevant principles and steps.

Machine Vision Algorithms and Applications

Author: Carsten Steger,Markus Ulrich,Christian Wiedemann

Publisher: John Wiley & Sons

ISBN: 3527413650

Category: Science

Page: 516

View: 879

The second edition of this successful machine vision textbook is completely updated, revised and expanded by 15% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new cameras and image acquisition interfaces, 3D sensors and technologies, 3D object recognition and 3D image reconstruction. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13, a trial version of which is available from the authors' website.

Practical Machine Learning with Python

A Problem-Solver's Guide to Building Real-World Intelligent Systems

Author: Dipanjan Sarkar,Raghav Bali,Tushar Sharma

Publisher: Apress

ISBN: 1484232070

Category: Computers

Page: 530

View: 3117

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students

Practical Computer Vision with SimpleCV

Author: Kurt Demaagd,Anthony Oliver,Nathan Oostendorp,Katherine Scott

Publisher: "O'Reilly Media, Inc."

ISBN: 1449320368

Category: Computers

Page: 240

View: 9684

Learn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You’ll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional. Capture images from several sources, including webcams, smartphones, and Kinect Filter image input so your application processes only necessary information Manipulate images by performing basic arithmetic on pixel values Use feature detection techniques to focus on interesting parts of an image Work with several features in a single image, using the NumPy and SciPy Python libraries Learn about optical flow to identify objects that change between two image frames Use SimpleCV’s command line and code editor to run examples and test techniques

An Introduction to 3D Computer Vision Techniques and Algorithms

Author: Boguslaw Cyganek,J. Paul Siebert

Publisher: John Wiley & Sons

ISBN: 1119964474

Category: Science

Page: 504

View: 9016

Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is possible to take a collection of stereo-pair images of a scene and then automatically produce a photo-realistic, geometrically accurate digital 3D model. This book provides a comprehensive introduction to the methods, theories and algorithms of 3D computer vision. Almost every theoretical issue is underpinned with practical implementation or a working algorithm using pseudo-code and complete code written in C++ and MatLab®. There is the additional clarification of an accompanying website with downloadable software, case studies and exercises. Organised in three parts, Cyganek and Siebert give a brief history of vision research, and subsequently: present basic low-level image processing operations for image matching, including a separate chapter on image matching algorithms; explain scale-space vision, as well as space reconstruction and multiview integration; demonstrate a variety of practical applications for 3D surface imaging and analysis; provide concise appendices on topics such as the basics of projective geometry and tensor calculus for image processing, distortion and noise in images plus image warping procedures. An Introduction to 3D Computer Vision Algorithms and Techniques is a valuable reference for practitioners and programmers working in 3D computer vision, image processing and analysis as well as computer visualisation. It would also be of interest to advanced students and researchers in the fields of engineering, computer science, clinical photography, robotics, graphics and mathematics.

High-Frequency Trading

A Practical Guide to Algorithmic Strategies and Trading Systems

Author: Irene Aldridge

Publisher: John Wiley and Sons

ISBN: 9780470579770

Category: Business & Economics

Page: 368

View: 9998

A hands-on guide to the fast and ever-changing world of high-frequency, algorithmic trading Financial markets are undergoing rapid innovation due to the continuing proliferation of computer power and algorithms. These developments have created a new investment discipline called high-frequency trading. This book covers all aspects of high-frequency trading, from the business case and formulation of ideas through the development of trading systems to application of capital and subsequent performance evaluation. It also includes numerous quantitative trading strategies, with market microstructure, event arbitrage, and deviations arbitrage discussed in great detail. Contains the tools and techniques needed for building a high-frequency trading system Details the post-trade analysis process, including key performance benchmarks and trade quality evaluation Written by well-known industry professional Irene Aldridge Interest in high-frequency trading has exploded over the past year. This book has what you need to gain a better understanding of how it works and what it takes to apply this approach to your trading endeavors.

A Practical Introduction to Computer Vision with OpenCV

Author: Kenneth Dawson-Howe

Publisher: John Wiley & Sons

ISBN: 111884873X

Category: Computers

Page: 240

View: 707

Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries Computer Vision is a rapidly expanding area and it is becoming progressively easier for developers to make use of this field due to the ready availability of high quality libraries (such as OpenCV 2). This text is intended to facilitate the practical use of computer vision with the goal being to bridge the gap between the theory and the practical implementation of computer vision. The book will explain how to use the relevant OpenCV library routines and will be accompanied by a full working program including the code snippets from the text. This textbook is a heavily illustrated, practical introduction to an exciting field, the applications of which are becoming almost ubiquitous. We are now surrounded by cameras, for example cameras on computers & tablets/ cameras built into our mobile phones/ cameras in games consoles; cameras imaging difficult modalities (such as ultrasound, X-ray, MRI) in hospitals, and surveillance cameras. This book is concerned with helping the next generation of computer developers to make use of all these images in order to develop systems which are more intuitive and interact with us in more intelligent ways. Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries Offers an introduction to computer vision, with enough theory to make clear how the various algorithms work but with an emphasis on practical programming issues Provides enough material for a one semester course in computer vision at senior undergraduate and Masters levels Includes the basics of cameras and images and image processing to remove noise, before moving on to topics such as image histogramming; binary imaging; video processing to detect and model moving objects; geometric operations & camera models; edge detection; features detection; recognition in images Contains a large number of vision application problems to provide students with the opportunity to solve real problems. Images or videos for these problems are provided in the resources associated with this book which include an enhanced eBook

Bioinformatics

A Practical Guide to the Analysis of Genes and Proteins

Author: Andreas D. Baxevanis,B. F. Francis Ouellette

Publisher: John Wiley & Sons

ISBN: 0471461016

Category: Computers

Page: 504

View: 2876

"In this book, Andy Baxevanis and Francis Ouellette . . . have undertaken the difficult task of organizing the knowledge in this field in a logical progression and presenting it in a digestible form. And they have done an excellent job. This fine text will make a major impact on biological research and, in turn, on progress in biomedicine. We are all in their debt." —Eric Lander from the Foreword Reviews from the First Edition "...provides a broad overview of the basic tools for sequence analysis ... For biologists approaching this subject for the first time, it will be a very useful handbook to keep on the shelf after the first reading, close to the computer." —Nature Structural Biology "...should be in the personal library of any biologist who uses the Internet for the analysis of DNA and protein sequence data." —Science "...a wonderful primer designed to navigate the novice through the intricacies of in scripto analysis ... The accomplished gene searcher will also find this book a useful addition to their library ... an excellent reference to the principles of bioinformatics." —Trends in Biochemical Sciences This new edition of the highly successful Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins provides a sound foundation of basic concepts, with practical discussions and comparisons of both computational tools and databases relevant to biological research. Equipping biologists with the modern tools necessary to solve practical problems in sequence data analysis, the Second Edition covers the broad spectrum of topics in bioinformatics, ranging from Internet concepts to predictive algorithms used on sequence, structure, and expression data. With chapters written by experts in the field, this up-to-date reference thoroughly covers vital concepts and is appropriate for both the novice and the experienced practitioner. Written in clear, simple language, the book is accessible to users without an advanced mathematical or computer science background. This new edition includes: All new end-of-chapter Web resources, bibliographies, and problem sets Accompanying Web site containing the answers to the problems, as well as links to relevant Web resources New coverage of comparative genomics, large-scale genome analysis, sequence assembly, and expressed sequence tags A glossary of commonly used terms in bioinformatics and genomics Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, Second Edition is essential reading for researchers, instructors, and students of all levels in molecular biology and bioinformatics, as well as for investigators involved in genomics, positional cloning, clinical research, and computational biology.

Person Re-Identification

Author: Shaogang Gong,Marco Cristani,Shuicheng Yan,Chen Change Loy

Publisher: Springer Science & Business Media

ISBN: 144716296X

Category: Computers

Page: 445

View: 2834

The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. Features: introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms and examines the benefits of semantic attributes; describes how to segregate meaningful body parts from background clutter; examines the use of 3D depth images and contextual constraints derived from the visual appearance of a group; reviews approaches to feature transfer function and distance metric learning and discusses potential solutions to issues of data scalability and identity inference; investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference and describes techniques for improving post-rank search efficiency; explores the design rationale and implementation considerations of building a practical re-identification system.

A Practical Guide to Brain–Computer Interfacing with BCI2000

General-Purpose Software for Brain-Computer Interface Research, Data Acquisition, Stimulus Presentation, and Brain Monitoring

Author: Gerwin Schalk,Jürgen Mellinger

Publisher: Springer Science & Business Media

ISBN: 9781849960922

Category: Computers

Page: 260

View: 1681

What Is BCI2000? BCI2000 is a general-purpose software platform for brain–computer interface (BCI) research. It can also be used for a wide variety of data acquisition, stimulus p- sentation, and brain monitoring applications. BCI2000 has been in development since 2000 in a project led by the Brain–Computer Interface R&D Program at the Wadsworth Center of the New York State Department of Health in Albany, New York, USA, with substantial contributions by the Institute of Medical Psychology and Behavioral Neurobiology at the University of Tübingen, Germany. In addition, many laboratories around the world, most notably the BrainLab at Georgia State University in Atlanta, Georgia, and Fondazione Santa Lucia in Rome, Italy, have also played an important role in the project’s development. Mission The mission of the BCI2000 project is to facilitate research and the development of applications in all areas that depend on real-time acquisition, processing, and feedback of biosignals. Vision Our vision is that BCI2000 will become a widely used software tool for diverse areas of research and development.

A Practical Guide to Data Mining for Business and Industry

Author: Andrea Ahlemeyer-Stubbe,Shirley Coleman

Publisher: John Wiley & Sons

ISBN: 1118763378

Category: Mathematics

Page: 328

View: 5923

Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

Hands-On Natural Language Processing with Python

A practical guide to applying deep learning architectures to your NLP applications

Author: Rajesh Arumugam,Rajalingappaa Shanmugamani

Publisher: Packt Publishing Ltd

ISBN: 1789135915

Category: Computers

Page: 312

View: 5404

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Computer Vision

Algorithms and Applications

Author: Richard Szeliski

Publisher: Springer Science & Business Media

ISBN: 9781848829350

Category: Computers

Page: 812

View: 2952

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

A Practical Guide to Designing Expert Systems

Author: Sholom M. Weiss,Casimir A. Kulikowski

Publisher: Rowman & Littlefield Pub Incorporated

ISBN: N.A

Category: Education

Page: 174

View: 9240

This book offers a practical introduction to expert systems and is designed not only for computer programmers but for all those who want to know how expert systems are structured and what they can do.

The LabVIEW Style Book

Author: Peter A. Blume

Publisher: Pearson Education

ISBN: 9780132797276

Category: Technology & Engineering

Page: 400

View: 3252

This is the eBook version of the print title. The illustrations are in color for this eBook version. Drawing on the experiences of a world-class LabVIEW development organization, The LabVIEW Style Book is the definitive guide to best practices in LabVIEW development. Leading LabVIEW development manager Peter A. Blume presents practical guidelines or “rules” for optimizing every facet of your applications: ease of use, efficiency, readability, simplicity, performance, maintainability, and robustness. Blume explains each style rule thoroughly, presenting realistic examples and illustrations. He even presents “nonconforming” examples that show what not to do—and why not. While the illustrations in the print book are in black and white, you can download full-color versions from the publisher web site for free.

Open Source Security Tools

Practical Applications for Security

Author: Tony Howlett

Publisher: Prentice Hall PTR

ISBN: N.A

Category: Computers

Page: 578

View: 2313

An introduction to Open source security tools covers such topics as installing an open source firewall, using sniffers and network-intrusion systems, scanning ports, and encrypting communications.