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Python: Real World Machine Learning
book

Python: Real World Machine Learning

by Prateek Joshi, John Hearty, Bastiaan Sjardin, Luca Massaron, Alberto Boschetti
November 2016
Beginner to intermediate
941 pages
21h 55m
English
Packt Publishing
Content preview from Python: Real World Machine Learning

Chapter 9. Image Content Analysis

In this chapter, we will cover the following recipes:

  • Operating on images using OpenCV-Python
  • Detecting edges
  • Histogram equalization
  • Detecting corners
  • Detecting SIFT feature points
  • Building Star feature detector
  • Creating features using visual codebook and vector quantization
  • Training an image classifier using Extremely Random Forests
  • Building an object recognizer

Introduction

Computer Vision is a field that studies how to process, analyze, and understand the contents of visual data. In image content analysis, we use a lot of Computer Vision algorithms to build our understanding of the objects in the image. Computer Vision covers various aspects of image analysis, such as object recognition, shape analysis, pose estimation, ...

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Publisher Resources

ISBN: 9781787123212Supplemental ContentPurchase Link