finelybookMore Information
Learn
Stay up-to-date with algorithmic design approaches for complex computer vision tasks
Work with OpenCV's most up-to-date API through various projects
Understand 3D scene reconstruction and Structure from Motion (SfM)
Study camera calibration and overlay augmented reality (AR) using the ArUco module
Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision algorithms and explore deep learning and face detection
Authors: David Millan Escriva - Prateek Joshi - Vinicius G. Mendonca - Roy Shilkrot
ISBN-10 书号: 1838644679
ISBN-13 书号: 9781838644673
Publisher Finelybook 出版日期: 2019-03-26
pages 页数: 538 pages
Book Description
Create CMake scripts to compile your C++ application
Explore segmentation and feature extraction techniques
Remove backgrounds from static scenes to identify moving objects for surveillance
Work with new OpenCV functions to detect and recognize text with Tesseract
About
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.
Whether you're completely new to computer vision or already have basic knowledge of its concepts,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 get an understanding of how 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 Escrivá
Learn OpenCV 4 By Building Projects Second Edition by David Millán Escrivá,Vinícius G. Mendonça,and Prateek Joshi
Features
Discover best practices for engineering and maintaining OpenCV projects
Explore important deep learning tools for image classification
Understand basic image matrix formats and filters
contents
1 Getting Started with OpenCV
2 An Introduction to the Basics of OpenCV
3 Learning Graphical User Interfaces
4 Delving into Histogram and Filters
5 Automated Optical Inspection,Object Segmentation,and Detection
6 Learning Object Classification
7 Detecting Face Parts and Overlaying Masks
8 Video Surveillance,Background Modeling,and Morphological Operations
9 Learning Object Tracking
10 Developing Segmentation Algorithms for Text Recognition
11 Text Recognition with Tesseract
12 Deep Learning with OpenCV
13 Cartoonifier and Skin Color Analysis on the RaspberryPi
14 Explore Structure from Motion with the SfM Module
15 Face Landmark and Pose with the Face Module
16 Number Plate Recognition with Deep Convolutional Networks
17 Face Detection and Recognition with the DNN Module
18 Android Camera Calibration and AR Using the ArUco Module
19 iOS Panoramas with the Stitching Module
20 Finding the Best OpenCV Algorithm for the Job
21 Avoiding Common Pitfalls in OpenCV
