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

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

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python. Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills. Learn techniques used in robot navigation, medical image analysis, and other computer vision applications Work with image mappings and transforms, such as texture warping and panorama creation Compute 3D reconstructions from several images of the same scene Organize images based on similarity or content, using clustering methods Build efficient image retrieval techniques to search for images based on visual content Use algorithms to classify image content and recognize objects Access the popular OpenCV library through a Python interface

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

A practical, project-based tutorial for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python.OpenCV Computer Vision with Python is written for Python developers who are new to computer vision and want a practical guide to teach them the essentials. Some understanding of image data (for example, pixels and color channels) would be beneficial. At a minimum you will need access to at least one webcam. Certain exercises require additional hardware like a second webcam, a Microsoft Kinect or an OpenNI-compliant depth sensor such as the Asus Xtion PRO.

OpenCV is a famous computer vision library, used to analyze and transform copious amounts of image data, even in real time and on a mobile device. This book focuses on leveraging mobile platforms to build interactive and useful applications. The book starts off with an introduction to OpenCV and Android and how they interact with each other using OpenCV's Java API. You'll also discover basic image processing techniques such as erosion and dilation of images, before walking through how to build more complex applications, such as object detection, image stitching, and face detection. As you progress, you will be introduced to OpenCV's machine learning framework, enabling you to make your applications smarter. The book ends with a short chapter covering useful Android tips and tricks and some common errors and solutions that people might face while building an application. By the end of the book, readers will have gained more expertise in building their own OpenCV projects for the Android platform and integrating OpenCV application programming into existing projects.

Strategies for building large systems that can be easily adapted for new situations with only minor programming modifications. Time pressures encourage programmers to write code that works well for a narrow purpose, with no room to grow. But the best systems are evolvable; they can be adapted for new situations by adding code, rather than changing the existing code. The authors describe techniques they have found effective--over their combined 100-plus years of programming experience--that will help programmers avoid programming themselves into corners. The authors explore ways to enhance flexibility by: Organizing systems using combinators to compose mix-and-match parts, ranging from small functions to whole arithmetics, with standardized interfaces Augmenting data with independent annotation layers, such as units of measurement or provenance Combining independent pieces of partial information using unification or propagation Separating control structure from problem domain with domain models, rule systems and pattern matching, propagation, and dependency-directed backtracking Extending the programming language, using dynamically extensible evaluators

The world of Raspberry Pi is evolving quickly, with many new interface boards and software libraries becoming available all the time. In this cookbook, prolific hacker and author Simon Monk provides more than 200 practical recipes for running this tiny low-cost computer with Linux, programming it with Python, and hooking up sensors, motors, and other hardware--including Arduino. Make sure to check out 10 of the over 60 video recipes for this book at: http://razzpisampler.oreilly.com/ You can purchase all recipes at:

Thinking about laser eye surgery? Tired of glasses and contacts? Take a look at this easy-to-follow, step-by-step method for improving poor vision. Hackett's innovative self-help guide includes a basic 12-week program of simple routines and drills that are recommended for correcting nearsightedness, farsightedness, crossed eyes, color-blindness, glaucoma, cataracts, and other serious eye problems. Incorporating Dr. William H. Bates' treatment of systematic exercise and training — techniques generally applied in treating and rehabilitating handicapped patients — the text suggests that relaxation, eyesight training, and skillful use of psychological factors are important elements that can possibly lead to improved eye functions. Bates, a practicing New York City ophthalmologist, first demonstrated his method of improving defective vision in the 1920s. Since then, thousands of people have been helped by methods devised by the doctor and his pupils. A useful aid for anyone experiencing problems with their vision, this practical guide will also be of value to healthcare specialists.

Combining coverage of the key concepts and tools within phonetics and phonology with a systematic introduction to Praat, this textbook provides a lively and engaging 'way in' to the discipline. The author first covers the fundamentals of the articulatory and acoustic aspects of speech and introduces Praat as the main tool for examining and visualising speech. Next, the unit of analysis is gradually expanded (from syllables to words to turns and dialogues) and excerpts of real dialogues exemplify the core concepts for discovering how speech works. The final part of the book brings all the concepts and notions together with commentaries to the transcription of several short excerpts of dialogues. This book will be essential reading for students on undergraduate courses in phonetics and phonology.