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OpenCV Android Programming By Example.

Annotation

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Muhammad, Amgad
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Packt Publishing, 2015.
Temas:
Acceso en línea:Texto completo

MARC

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520 8 |a Annotation  |b Develop vision-aware and intelligent Android applications with the robust OpenCV libraryAbout This Book This is the most up-to-date book on OpenCV Android programming on the market at the moment. There is no direct competition for our title. Based on a technology that is increasing in popularity, proven by activity in forums related to this topic. This book uniquely covers applications such as the Panoramic viewer and Automatic Selfie, among others. Who This Book Is ForIf you are an Android developer and want to know how to implement vision-aware applications using OpenCV, then this book is definitely for you. It would be very helpful if you understand the basics of image processing and computer vision, but no prior experience is requiredWhat You Will Learn Identify and install all the elements needed to start building vision-aware Android applications Explore image representation, colored and gray scale Recognize and apply convolution operations and filtering to deal with noisy data Use different shape analysis techniques Extract and identify interest points in an image Understand and perform object detection Run native computer vision algorithms and gain performance boostsIn DetailStarting from the basics of computer vision and OpenCV, we'll take you all the way to creating exciting applications. You will discover that, though computer vision is a challenging subject, the ideas and algorithms used are simple and intuitive, and you will appreciate the abstraction layer that OpenCV uses to do the heavy lifting for you. Packed with many examples, the book will help you understand the main data structures used within OpenCV, and how you can use them to gain performance boosts. Next we will discuss and use several image processing algorithms such as histogram equalization, filters, and color space conversion. You then will learn about image gradients and how they are used in many shape analysis techniques such as edge detection, Hough Line Transform, and Hough Circle Transform. In addition to using shape analysis to find things in images, you will learn how to describe objects in images in a more robust way using different feature detectors and descriptors. By the end of this book, you will be able to make intelligent decisions using the famous Adaboost learning algorithm. Style and approachAn easy-to-follow tutorial packed with hands-on examples. Each topic is explained and placed in context, and the book supplies full details of the concepts used for added proficiency. 
505 0 |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Yourself Ready; Installing Tegra Android Development Pack; Downloading and installing TADP; TADP post-installation configuration; Installing emulator system images; Configuring Eclipse to work with NDK; NDK verification; Installing the OpenCV and Android development environment manually; Java SE Development Kit 6; Android Studio; Android SDK; Eclipse IDE; ADT and CDT plugins for Eclipse; Android NDK; Downloading Android NDK; Installing and configuring Android NDK. 
505 8 |a Building native code using EclipseOpenCV4Android SDK; Understanding how NDK works; An overview of NDK; A simple example of NDK; Building your first Android project with OpenCV; HelloVisionWorld Android application; Creating a project in Eclipse; Creating a project in Android Studio; Summary; Chapter 2: App 1 -- Building Your Own Darkroom; Digital images; Color spaces; The Mat class; Basic Mat operations; Processing the images stored on your phone; Loading an image to a Mat object; UI definitions; Reading an image using OpenCV; Calculating an image histogram; What are histograms? 
505 8 |a Understanding histogram componentsEnhancing the image contrast; Understanding histogram equalization; Enhancing grayscale images; Enhancing an HSV image; Enhancing an RGB image; Summary; Chapter 3: App 2 -- Software Scanner; Spatial filtering; Understanding convolution and linear filtering; Removing noise; The averaging filter; The Gaussian filter; The median filter; UI definitions; Applying filters to reduce image noise; Finding edges; The Sobel edge detector; The Canny edge detector; UI definitions; Applying the Sobel filter to find edges; Using the Canny edge detector; Detecting shapes. 
505 8 |a Understanding the Hough line transformDetecting lines using Hough transform; UI definitions; Detecting and drawing lines; Detecting circles using Hough transform; UI definitions; Detecting and drawing circles; Summary; Chapter 4: App 2 -- Applying Perspective Correction; Image transformations and perspective correction; Translation; Rotation and translation; Scaled rotation; Affine; Perspective transformation; Rigid perspective correction; UI definitions; Estimating the perspective transformation using the object bounding box; Flexible perspective correction; UI definitions. 
505 8 |a Applying flexible perspective correctionManual perspective correction; UI definitions; Selecting the corners manually; Summary; Chapter 5: App 3 -- Panoramic Viewer; Image features; Feature detectors; Understanding the Harris corner detector; Understanding the FAST corner detector; Understanding the ORB feature detector; Feature description and matching; Understanding BRIEF and ORB feature descriptors; Understanding the BRISK feature descriptor; Understanding the FREAK feature descriptor; Matching the features; Working with feature matching; Native feature matching; Stitching two images. 
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