Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Book Image

Learning OpenCV 3 Computer Vision with Python (Update)

Overview of this book

Related Content you might be interested in

Current Title:

Small book image
Learning OpenCV 3 Computer Vision with Python (Update)
Sep, 2015 | 266 pages
No titles found
Table of Contents (16 chapters)
Learning OpenCV 3 Computer Vision with Python Second Edition
Learning OpenCV 3 Computer Vision with Python Second Edition
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Setting Up OpenCV
Setting Up OpenCV
Choosing and using the right setup tools
Installing the Contrib modules
Running samples
Finding documentation, help, and updates
Summary
2
Handling Files, Cameras, and GUIs
Handling Files, Cameras, and GUIs
Basic I/O scripts
Project Cameo (face tracking and image manipulation)
Cameo – an object-oriented design
Summary
3
Processing Images with OpenCV 3
Processing Images with OpenCV 3
Converting between different color spaces
The Fourier Transform
Creating modules
Edge detection
Custom kernels – getting convoluted
Modifying the application
Edge detection with Canny
Contour detection
Contours – bounding box, minimum area rectangle, and minimum enclosing circle
Contours – convex contours and the Douglas-Peucker algorithm
Line and circle detection
Detecting shapes
Summary
4
Depth Estimation and Segmentation
Depth Estimation and Segmentation
Creating modules
Capturing frames from a depth camera
Creating a mask from a disparity map
Masking a copy operation
Depth estimation with a normal camera
Object segmentation using the Watershed and GrabCut algorithms
Summary
5
Detecting and Recognizing Faces
Detecting and Recognizing Faces
Conceptualizing Haar cascades
Getting Haar cascade data
Using OpenCV to perform face detection
Summary
6
Retrieving Images and Searching Using Image Descriptors
Retrieving Images and Searching Using Image Descriptors
Feature detection algorithms
Summary
7
Detecting and Recognizing Objects
Detecting and Recognizing Objects
Object detection and recognition techniques
Detecting cars
Summary
8
Tracking Objects
Tracking Objects
Detecting moving objects
Background subtractors – KNN, MOG2, and GMG
CAMShift
The Kalman filter
Summary
9
Neural Networks with OpenCV – an Introduction
Neural Networks with OpenCV – an Introduction
Artificial neural networks
The structure of an ANN
ANNs in OpenCV
Handwritten digit recognition with ANNs
Possible improvements and potential applications
Summary
Index
Index

Credits

Authors

Joe Minichino

Joseph Howse

Reviewers

Nandan Banerjee

Tian Cao

Brandon Castellano

Haojian Jin

Adrian Rosebrock

Commissioning Editor

Akram Hussain

Acquisition Editors

Vivek Anantharaman

Prachi Bisht

Content Development Editor

Ritika Singh

Technical Editors

Novina Kewalramani

Shivani Kiran Mistry

Copy Editor

Sonia Cheema

Project Coordinator

Milton Dsouza

Proofreader

Safis Editing

Indexer

Monica Ajmera Mehta

Graphics

Disha Haria

Production Coordinator

Arvindkumar Gupta

Cover Work

Arvindkumar Gupta

Previous Section
Next Chapter