Learn OpenCV 4 by building projects :: build real-world computer vision and image processing applications with OpenCV and C++ /
OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the b...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2018.
|
| Ausgabe: | Second edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the basic OpenCV concepts and algorithms. |
| Beschreibung: | Previous edition published: 2016. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781789347623 1789347629 |
Internformat
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| 246 | 3 | |a Learn Open Computer Vision four by building projects | |
| 246 | 3 | 0 | |a Build real-world computer vision and image processing applications with OpenCV and C++ |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2018. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 500 | |a Previous edition published: 2016. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 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 | |
| 520 | |a OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the basic OpenCV concepts and algorithms. | ||
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| contents | 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 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 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 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 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 |
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| discipline | Informatik |
| edition | Second edition. |
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| spelling | Millán Escrivá, David, author. Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi. Learn Open Computer Vision four by building projects Build real-world computer vision and image processing applications with OpenCV and C++ Second edition. Birmingham, UK : Packt Publishing, 2018. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from title page (Safari, viewed February 1, 2019). Previous edition published: 2016. Includes bibliographical references and index. 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 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 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 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 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 OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the basic OpenCV concepts and algorithms. Computer vision. http://id.loc.gov/authorities/subjects/sh85029549 OpenCV (Computer program language) http://id.loc.gov/authorities/subjects/sh2016000128 Image processing. http://id.loc.gov/authorities/subjects/sh85064446 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Vision par ordinateur. OpenCV (Langage de programmation) Traitement d'images. Algorithmes. image processing. aat algorithms. aat COMPUTERS General. bisacsh Computer algorithms fast Computer vision fast Image processing fast OpenCV (Computer program language) fast Mendonça, Vinícius G., author. Joshi, Prateek, author. http://id.loc.gov/authorities/names/no2016034220 has work: Learn OpenCV 4 by building projects (Text) https://id.oclc.org/worldcat/entity/E39PCGpQFxDJP7kxXp3jMDXJH3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Millán Escrivá, David Learn OpenCV 4 by Building Projects : Build Real-World Computer Vision and Image Processing Applications with OpenCV and C++, 2nd Edition Birmingham : Packt Publishing Ltd,c2018 9781789341225 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1950548 Volltext |
| spellingShingle | Millán Escrivá, David Mendonça, Vinícius G. Joshi, Prateek Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / 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 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 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 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 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 Computer vision. http://id.loc.gov/authorities/subjects/sh85029549 OpenCV (Computer program language) http://id.loc.gov/authorities/subjects/sh2016000128 Image processing. http://id.loc.gov/authorities/subjects/sh85064446 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Vision par ordinateur. OpenCV (Langage de programmation) Traitement d'images. Algorithmes. image processing. aat algorithms. aat COMPUTERS General. bisacsh Computer algorithms fast Computer vision fast Image processing fast OpenCV (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85029549 http://id.loc.gov/authorities/subjects/sh2016000128 http://id.loc.gov/authorities/subjects/sh85064446 http://id.loc.gov/authorities/subjects/sh91000149 https://id.nlm.nih.gov/mesh/D000465 |
| title | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / |
| title_alt | Learn Open Computer Vision four by building projects Build real-world computer vision and image processing applications with OpenCV and C++ |
| title_auth | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / |
| title_exact_search | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / |
| title_full | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi. |
| title_fullStr | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi. |
| title_full_unstemmed | Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi. |
| title_short | Learn OpenCV 4 by building projects : |
| title_sort | learn opencv 4 by building projects build real world computer vision and image processing applications with opencv and c |
| title_sub | build real-world computer vision and image processing applications with OpenCV and C++ / |
| topic | Computer vision. http://id.loc.gov/authorities/subjects/sh85029549 OpenCV (Computer program language) http://id.loc.gov/authorities/subjects/sh2016000128 Image processing. http://id.loc.gov/authorities/subjects/sh85064446 Computer algorithms. http://id.loc.gov/authorities/subjects/sh91000149 Algorithms https://id.nlm.nih.gov/mesh/D000465 Vision par ordinateur. OpenCV (Langage de programmation) Traitement d'images. Algorithmes. image processing. aat algorithms. aat COMPUTERS General. bisacsh Computer algorithms fast Computer vision fast Image processing fast OpenCV (Computer program language) fast |
| topic_facet | Computer vision. OpenCV (Computer program language) Image processing. Computer algorithms. Algorithms Vision par ordinateur. OpenCV (Langage de programmation) Traitement d'images. Algorithmes. image processing. algorithms. COMPUTERS General. Computer algorithms Computer vision Image processing |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1950548 |
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