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OpenCV essentials : acquire, process, and analyze visual content to build full-fledged imaging applications using OpenCV /
This book is intended for C++ developers who want to learn how to implement the main techniques of OpenCV and get started with it quickly. Working experience with computer vision / image processing is expected.
| Clasificación: | Libro Electrónico |
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| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Brimingham, UK :
Packt Pub.,
2014.
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started; Setting up OpenCV; Compiled versus precompiled library; Configuring OpenCV with Cmake; Building and installing the library; Quick recipe for setting up OpenCV; API concepts and basic datatypes; Our first program
- reading and writing images and videos; The qmake project file; Reading and playing a video file; Live input from a camera; Summary; Chapter 2: Something We Look at
- Graphical User Interfaces; Using OpenCV''s highgui module; Text and drawing.
- Selecting regionsUsing Qt-based functions; Text overlays and status bar; The properties dialog; Windows properties; Qt images; Summary; Chapter 3: First Things First
- Image Processing; Pixel-level access and common operations; Image histogram; Histogram equalization; Brightness and contrast modeling; Histogram matching and LUT; Conversion from RGB to other color spaces; Filtering with the retina model; Arithmetic and geometrical transforms; Arithmetic transform; Geometrical transforms; Summary; What else?; Chapter 4: What''s in the Image? Segmentation; Thresholding.
- Contours and connected componentsFlood fill; Watershed segmentation; GrabCut; Summary; What else?; Chapter 5: Focusing on the Interesting 2D Features; Interest points; Feature detectors; The FAST detector; The SURF detector; The ORB detector; The KAZE and AKAZE detectors; Feature descriptor extractors; Descriptor matchers; Matching the SURF descriptors; Matching the AKAZE descriptors; Summary; What else?; Chapter 6: Where''s Wally? Object Detection; Object detection; Detecting objects with OpenCV; Cascades are beautiful; Object detection using cascades; Training your own cascade; Latent SVM.
- Scene text detectionSummary; What else?; Chapter 7: What Is He Doing? Motion; Motion history; Reading video sequences; The Lucas-Kanade optical flow; The Gunnar-Farneback optical flow; The Mean-Shift tracker; The CamShift tracker; The Motion templates; The Motion history template; The Motion gradient; The Background subtraction technique; Image alignment; Summary; What else?; Chapter 8: Advanced Topics; Machine learning; The KNN classifier; The Random Forest classifier; SVM for classification; What about GPUs?; Setting up OpenCV with CUDA; Configuring the OpenCV build.
- Building and installing the libraryA quick recipe for setting up OpenCV with CUDA; Our first GPU-based program; Going real time; Performance; Summary; What else?; Index.