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OpenCV by example : enhance your understanding of computer vision and image processing by developing real-world projects in OpenCV 3 /
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2016.
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with OpenCV; Understanding the human visual system; How do humans understand image content?; Why is it difficult for machines to understand image content?; What can you do with OpenCV?; In-built data structures and input/output; Image processing operations; Building GUI; Video analysis; 3D reconstruction; Feature extraction; Object detection; Machine learning; Computational photography; Shape analysis; Optical flow algorithms; Face and object recognition
- Surface matchingText detection and recognition; Installing OpenCV; Windows; Mac OS X; Linux; Summary; Chapter 2: An Introduction to the Basics of OpenCV; Basic CMake configuration files; Creating a library; Managing dependencies; Making the script more complex; Images and matrices; Reading/writing images; Reading videos and cameras; Other basic object types; The vec object type; The Scalar object type; The Point object type; The Size object type; The Rect object type; RotatedRect object type; Basic matrix operations; Basic data persistence and storage; Writing to a file storage; Summary
- Chapter 3: Learning the Graphical User Interface and Basic FilteringIntroducing the OpenCV user interface; A basic graphical user interface with OpenCV; The graphical user interface with QT; Adding slider and mouse events to our interfaces; Adding buttons to a user interface; OpenGL support; Summary; Chapter 4: Delving into Histograms and Filters; Generating a CMake script file; Creating the Graphical User Interface; Drawing a histogram; Image color equalization; Lomography effect; The cartoonize effect; Summary; Chapter 5: Automated Optical Inspection, Object Segmentation, and Detection
- Isolating objects in a sceneCreating an application for AOI; Preprocessing the input image; Noise removal; Removing the background using the light pattern for segmentation; The thresholding operation; Segmenting our input image; The connected component algorithm; The findContours algorithm; Summary; Chapter 6: Learning Object Classification; Introducing machine learning concepts; Computer Vision and the machine learning workflow; Automatic object inspection classification example; Feature extraction; Training an SVM model; Input image prediction; Summary
- Chapter 7: Detecting Face Parts and Overlaying MasksUnderstanding Haar cascades; What are integral images?; Overlaying a facemask in a live video; What happened in the code?; Get your sunglasses on; Looking inside the code; Tracking your nose, mouth, and ears; Summary; Chapter 8: Video Surveillance, Background Modeling, and Morphological Operations; Understanding background subtraction; Naive background subtraction; Does it work well?; Frame differencing; How well does it work?; The Mixture of Gaussians approach; What happened in the code?; Morphological image processing