Practical Guide to Machine Vision Software

An Introduction with LabVIEW

Author: Kye-Si Kwon

Publisher: John Wiley & Sons


Category: Computers

Page: 296

View: 401

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.

Exam Prep for: Practical Guide to Machine Vision Software

Author: David Mason

Publisher: Rico Publications


Category: Education

Page: 800

View: 854

5,600 Exam Prep questions and answers. Ebooks, Textbooks, Courses, Books Simplified as questions and answers by Rico Publications. Very effective study tools especially when you only have a limited amount of time. They work with your textbook or without a textbook and can help you to review and learn essential terms, people, places, events, and key concepts.

Mastering OpenCV 4 with Python

A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

Author: Alberto Fernández Villán

Publisher: Packt Publishing Ltd


Category: Computers

Page: 532

View: 201

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Practical Guide to Image Analysis

Author: ASM International

Publisher: Asm International


Category: Technology & Engineering

Page: 290

View: 230

Nine international specialists contribute information about the use of image analysis procedures to evaluate microstructural features. Coverage includes an historical overview of how quantitative image analysis developed; the evolution of current television computer-based analysis systems; the scien

Machine Learning for Mobile

Practical guide to building intelligent mobile applications powered by machine learning

Author: Revathi Gopalakrishnan

Publisher: Packt Publishing Ltd


Category: Computers

Page: 274

View: 213

Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease Key Features Build smart mobile applications for Android and iOS devices Use popular machine learning toolkits such as Core ML and TensorFlow Lite Explore cloud services for machine learning that can be used in mobile apps Book Description Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices. What you will learn Build intelligent machine learning models that run on Android and iOS Use machine learning toolkits such as Core ML, TensorFlow Lite, and more Learn how to use Google Mobile Vision in your mobile apps Build a spam message detection system using Linear SVM Using Core ML to implement a regression model for iOS devices Build image classification systems using TensorFlow Lite and Core ML Who this book is for If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus

A Computational Introduction to Digital Image Processing

Author: Alasdair McAndrew

Publisher: CRC Press


Category: Computers

Page: 535

View: 737

Highly Regarded, Accessible Approach to Image Processing Using Open-Source and Commercial Software A Computational Introduction to Digital Image Processing, Second Edition explores the nature and use of digital images and shows how they can be obtained, stored, and displayed. Taking a strictly elementary perspective, the book only covers topics that involve simple mathematics yet offer a very broad and deep introduction to the discipline. New to the Second Edition This second edition provides users with three different computing options. Along with MATLAB®, this edition now includes GNU Octave and Python. Users can choose the best software to fit their needs or migrate from one system to another. Programs are written as modular as possible, allowing for greater flexibility, code reuse, and conciseness. This edition also contains new images, redrawn diagrams, and new discussions of edge-preserving blurring filters, ISODATA thresholding, Radon transform, corner detection, retinex algorithm, LZW compression, and other topics. Principles, Practices, and Programming Based on the author’s successful image processing courses, this bestseller is suitable for classroom use or self-study. In a straightforward way, the text illustrates how to implement imaging techniques in MATLAB, GNU Octave, and Python. It includes numerous examples and exercises to give students hands-on practice with the material.

Alan Turing, Enigma

Author: Andrew Hodges

Publisher: Springer Verlag


Category: Biography & Autobiography

Page: 662

View: 841

Alan Turing, Enigma ist die Biographie des legendAren britischen Mathematikers, Logikers, Kryptoanalytikers und Computerkonstrukteurs Alan Mathison Turing (1912-1954). Turing war einer der bedeutendsten Mathematiker dieses Jahrhunderts und eine hAchst exzentrische PersAnlichkeit. Er gilt seit seiner 1937 erschienenen Arbeit "On Computable Numbers," in der er das Prinzip des abstrakten Universalrechners entwickelte, als der Erfinder des Computers. Er legte auch die Grundlagen fA1/4r das heute "KA1/4nstliche Intelligenz" genannte Forschungsgebiet. Turings zentrale Frage "Kann eine Maschine denken?" war das Motiv seiner Arbeit und wird die SchlA1/4sselfrage des Umgangs mit dem Computer werden. Die bis 1975 geheimgehaltene TAtigkeit Turings fA1/4r den britischen Geheimdienst, die zur EntschlA1/4sselung des deutschen Funkverkehrs fA1/4hrte, trug entscheidend zum Verlauf und Ausgang des Zweiten Weltkriegs bei.

Machine Vision

The Eyes of Automation : a Manager's Practical Guide

Author: Jack Hollingum



Category: Computer vision

Page: 113

View: 761

The Essential Guide to Video Processing

Author: Alan C. Bovik

Publisher: Academic Press


Category: Technology & Engineering

Page: 778

View: 473

This comprehensive and state-of-the art approach to video processing gives engineers and students a comprehensive introduction and includes full coverage of key applications: wireless video, video networks, video indexing and retrieval and use of video in speech processing. Containing all the essential methods in video processing alongside the latest standards, it is a complete resource for the professional engineer, researcher and graduate student. Numerous conceptual and numerical examples All the latest standards are thoroughly covered: MPEG-1, MPEG-2, MPEG-4, H.264 and AVC Coverage of the latest techniques in video security "Like its sister volume "The Essential Guide to Image Processing," Professor Bovik’s Essential Guide to Video Processing provides a timely and comprehensive survey, with contributions from leading researchers in the area. Highly recommended for everyone with an interest in this fascinating and fast-moving field." —Prof. Bernd Girod, Stanford University, USA * Edited by a leading person in the field who created the IEEE International Conference on Image Processing, with contributions from experts in their fields. * Numerous conceptual and numerical examples *All the latest standards are thoroughly covered: MPEG-1, MPEG-2, MPEG-4, H.264 and AVC. * Coverage of the latest techniques in video security