Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection

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Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms

Key FeaturesDiscover best practices for engineering and maintaining OpenCV projectsExplore important deep learning tools for image classificationUnderstand basic image matrix formats and filtersBook Description

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.

This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you’ll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you’ll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books:

Mastering OpenCV 4 – Third Edition by Roy Shilkrot and David Millán EscriváLearn OpenCV 4 By Building Projects – Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek JoshiWhat you will learnStay up-to-date with algorithmic design approaches for complex computer vision tasksWork with OpenCV’s most up-to-date API through various projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay augmented reality (AR) using the ArUco moduleCreate CMake scripts to compile your C++ applicationExplore segmentation and feature extraction techniquesRemove backgrounds from static scenes to identify moving objects for surveillanceWork with new OpenCV functions to detect and recognize text with TesseractWho this book is for

If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.

Table of ContentsGetting Started with OpenCVAn Introduction to the Basics of OpenCVLearning Graphical User InterfacesDelving into Histogram and FiltersAutomated Optical Inspection, Object Segmentation, and DetectionLearning Object ClassificationDetecting Face Parts and Overlaying MasksVideo Surveillance, Background Modeling, and Morphological OperationsLearning Object TrackingDeveloping Segmentation Algorithms for Text RecognitionText Recognition with TesseractDeep Learning with OpenCVCartoonifier and Skin Color Analysis on the RaspberryPiExplore Structure from Motion with the SfM ModuleFace Landmark and Pose with the Face ModuleNumber Plate Recognition with Deep Convolutional NetworksFace Detection and Recognition with the DNN ModuleAndroid Camera Calibration and AR Using the ArUco ModuleiOS Panoramas with the Stitching ModuleFinding the Best OpenCV Algorithm for the JobAvoiding Common Pitfalls in OpenCV

ASIN ‏ : ‎ B07Q6R9L86
Publisher ‏ : ‎ Packt Publishing; 1st edition (26 March 2019)
Language ‏ : ‎ English
File size ‏ : ‎ 67.9 MB
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 540 pages
Page numbers source ISBN ‏ : ‎ 1838644679
Best Sellers Rank: #124,807 in Kindle Store (See Top 100 in Kindle Store) #90 in C++ Programming Language #101 in Programming Languages eTextbooks #1,022 in Computer Science (Kindle Store)
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