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Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection.
This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. By taking this Learning Path, you will be able to work on complex projects that involves image processing, motion detection, and image segmentation.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing Ltd,
2019.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Millán Escrivá, David. | |
| 245 | 1 | 0 | |a Building Computer Vision Projects with OpenCV 4 and C++ : |b Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| 260 | |a Birmingham : |b Packt Publishing Ltd, |c 2019. | ||
| 300 | |a 1 online resource (527 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Title Page; Copyright and Credits; About Packt; Contributors; 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?; Inbuilt data structures and input/output; Image processing operations; GUI; Video analysis; 3D reconstruction; Feature extraction; Object detection; Machine learning; Computational photography; Shape analysis; Optical flow algorithms; Face and object recognition; Surface matching | |
| 505 | 8 | |a Text detection and recognitionDeep learning; Installing OpenCV; Windows; Mac OS X; Linux; Summary; Chapter 2: An Introduction to the Basics of OpenCV; Technical requirements; Basic CMake configuration file; Creating a library; Managing dependencies; Making the script more complex; Images and matrices; Reading/writing images; Reading videos and cameras; Other basic object types; Vec object type; Scalar object type; Point object type; Size object type; Rect object type; RotatedRect object type; Basic matrix operations; Basic data persistence and storage; Writing to FileStorage; Summary | |
| 505 | 8 | |a Chapter 3: Learning Graphical User InterfacesTechnical requirements; Introducing the OpenCV user interface; Basic graphical user interface with OpenCV; Adding slider and mouse events to our interfaces; Graphic user interface with Qt; Adding buttons to the user interface; OpenGL support; Summary; Chapter 4: Delving into Histogram and Filters; Technical requirements; Generating a CMake script file; Creating the graphical user interface; Drawing a histogram; Image color equalization; Lomography effect; Cartoonize effect; Summary | |
| 505 | 8 | |a Chapter 5: Automated Optical Inspection, Object Segmentation, and DetectionTechnical requirements; Isolating objects in a scene; Creating an application for AOI; Preprocessing the input image; Noise removal; Removing the background using the light pattern for segmentation; Thresholding; Segmenting our input image; The connected components algorithm; The findContours algorithm; Summary; Chapter 6: Learning Object Classification; Technical requirements; Introducing machine learning concepts; OpenCV machine learning algorithms; Computer vision and the machine learning workflow | |
| 505 | 8 | |a Automatic object inspection classification exampleFeature extraction; Training an SVM model; Input image prediction; Summary; Chapter 7: Detecting Face Parts and Overlaying Masks; Technical requirements; Understanding Haar cascades; What are integral images?; Overlaying a face mask in a live video; What happened in the code?; Get your sunglasses on; Looking inside the code; Tracking the nose, mouth, and ears; Summary; Chapter 8: Video Surveillance, Background Modeling, and Morphological Operations; Technical requirements; Understanding background subtraction; Naive background subtraction | |
| 500 | |a Does it work well? | ||
| 520 | |a This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. By taking this Learning Path, you will be able to work on complex projects that involves image processing, motion detection, and image segmentation. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a OpenCV (Computer program language) | |
| 650 | 0 | |a Image processing. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 2 | |a Algorithms | |
| 650 | 6 | |a Vision par ordinateur. | |
| 650 | 6 | |a OpenCV (Langage de programmation) | |
| 650 | 6 | |a Traitement d'images. | |
| 650 | 6 | |a Algorithmes. | |
| 650 | 7 | |a image processing. |2 aat | |
| 650 | 7 | |a algorithms. |2 aat | |
| 650 | 7 | |a Programming & scripting languages: general. |2 bicssc | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a Pattern recognition. |2 bicssc | |
| 650 | 7 | |a Computer vision. |2 bicssc | |
| 650 | 7 | |a Computers. |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Computers. |x Programming Languages |x C. |2 bisacsh | |
| 650 | 7 | |a Computers. |x Computer Vision & Pattern Recognition. |2 bisacsh | |
| 650 | 7 | |a Computer algorithms |2 fast | |
| 650 | 7 | |a Computer vision |2 fast | |
| 650 | 7 | |a Image processing |2 fast | |
| 650 | 7 | |a OpenCV (Computer program language) |2 fast | |
| 700 | 1 | |a Joshi, Prateek. | |
| 700 | 1 | |a G. Mendonça, Vinícius. | |
| 700 | 1 | |a Shilkrot, Roy. | |
| 776 | 0 | 8 | |i Print version: |a Millán Escrivá, David. |t Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |d Birmingham : Packt Publishing Ltd, ©2019 |z 9781838644673 |
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