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OpenCV 3.x with Python By Example - Second Edition

You're reading from  OpenCV 3.x with Python By Example - Second Edition

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Pages 268 pages
Edition 2nd Edition
Languages
Authors (2):
Gabriel Garrido Calvo Gabriel Garrido Calvo
Profile icon Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Copyright and Credits
Contributors
Packt Upsell
Preface
1. Applying Geometric Transformations to Images 2. Detecting Edges and Applying Image Filters 3. Cartoonizing an Image 4. Detecting and Tracking Different Body Parts 5. Extracting Features from an Image 6. Seam Carving 7. Detecting Shapes and Segmenting an Image 8. Object Tracking 9. Object Recognition 10. Augmented Reality 11. Machine Learning by an Artificial Neural Network 1. Other Books You May Enjoy

Appendix 1. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition Robert Laganiere

ISBN: 978-1-78646-971-7

  • Install and create a program using the OpenCV library
  • Process an image by manipulating its pixels
  • Analyze an image using histograms
  • Segment images into homogenous regions and extract meaningful objects
  • Apply image filters to enhance image content
  • Exploit the image geometry in order to relay different views of a pictured scene
  • Calibrate the camera from different image observations
  • Detect people and objects in images using machine learning techniques
  • Reconstruct a 3D scene from images

Mastering OpenCV 3 - Second Edition Daniel Lélis Baggio, Shervin Emami, David Millán Escrivá, Khvedchenia Ievgen, Jason Saragih, Roy Shilkrot

ISBN: 978-1-78439-030-3

  • Execute basic image processing operations and cartoonify an image
  • Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text
  • Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video
  • Use OpenCV 3’s new 3D visualization framework to illustrate the 3D scene geometry
  • Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks
  • Train and predict pattern-recognition algorithms to decide whether an image is a number plate
  • Use POSIT for the six degrees of freedom head pose
  • Train a face recognition database using deep learning and recognize faces from that database
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