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.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham :
Packt Publishing Ltd,
2019.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | Does it work well? |
| Beschreibung: | 1 online resource (527 pages) |
| ISBN: | 1838641262 9781838641269 |
Internformat
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 | ||
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| 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. | ||
| 650 | 0 | |a Computer vision. |0 http://id.loc.gov/authorities/subjects/sh85029549 | |
| 650 | 0 | |a OpenCV (Computer program language) |0 http://id.loc.gov/authorities/subjects/sh2016000128 | |
| 650 | 0 | |a Image processing. |0 http://id.loc.gov/authorities/subjects/sh85064446 | |
| 650 | 0 | |a Computer algorithms. |0 http://id.loc.gov/authorities/subjects/sh91000149 | |
| 650 | 2 | |a Algorithms |0 https://id.nlm.nih.gov/mesh/D000465 | |
| 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. | |
| 758 | |i has work: |a Building computer vision projects with OpenCV4 and C++ (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFGPRBfP8bH6yDY7gbPXJP |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 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 |
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2093826 |3 Volltext |
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| author | Millán Escrivá, David |
| author2 | Joshi, Prateek G. Mendonça, Vinícius Shilkrot, Roy |
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| author_facet | Millán Escrivá, David Joshi, Prateek G. Mendonça, Vinícius Shilkrot, Roy |
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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 |
| ctrlnum | (OCoLC)1096232279 |
| dewey-full | 006.37 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.37 |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-4-EBA-on1096232279 |
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| indexdate | 2024-11-27T13:29:26Z |
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| publisher | Packt Publishing Ltd, |
| record_format | marc |
| spelling | Millán Escrivá, David. Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. Birmingham : Packt Publishing Ltd, 2019. 1 online resource (527 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Print version record. 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 Does it work well? 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. 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 Programming & scripting languages: general. bicssc Artificial intelligence. bicssc Pattern recognition. bicssc Computer vision. bicssc Computers. Intelligence (AI) & Semantics. bisacsh Computers. Programming Languages C. bisacsh Computers. Computer Vision & Pattern Recognition. bisacsh Computer algorithms fast Computer vision fast Image processing fast OpenCV (Computer program language) fast Joshi, Prateek. G. Mendonça, Vinícius. Shilkrot, Roy. has work: Building computer vision projects with OpenCV4 and C++ (Text) https://id.oclc.org/worldcat/entity/E39PCFGPRBfP8bH6yDY7gbPXJP https://id.oclc.org/worldcat/ontology/hasWork Print version: Millán Escrivá, David. Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. Birmingham : Packt Publishing Ltd, ©2019 9781838644673 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2093826 Volltext |
| spellingShingle | Millán Escrivá, David Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. 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 Programming & scripting languages: general. bicssc Artificial intelligence. bicssc Pattern recognition. bicssc Computer vision. bicssc Computers. Intelligence (AI) & Semantics. bisacsh Computers. Programming Languages C. bisacsh Computers. Computer Vision & Pattern Recognition. 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 | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_auth | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_exact_search | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_full | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_fullStr | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_full_unstemmed | Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| title_short | Building Computer Vision Projects with OpenCV 4 and C++ : |
| title_sort | building computer vision projects with opencv 4 and c implement complex computer vision algorithms and explore deep learning and face detection |
| title_sub | Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection. |
| 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 Programming & scripting languages: general. bicssc Artificial intelligence. bicssc Pattern recognition. bicssc Computer vision. bicssc Computers. Intelligence (AI) & Semantics. bisacsh Computers. Programming Languages C. bisacsh Computers. Computer Vision & Pattern Recognition. 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. Programming & scripting languages: general. Artificial intelligence. Pattern recognition. Computers. Intelligence (AI) & Semantics. Computers. Programming Languages C. Computers. Computer Vision & Pattern Recognition. Computer algorithms Computer vision Image processing |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2093826 |
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