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Python: End-to-end Data Analysis

You're reading from Python: End-to-end Data Analysis Leverage the power of Python to clean, scrape, analyze, and visualize your data

Product type Course

Published in May 2017

Publisher Packt

ISBN-13 9781788394697

Length 931 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (5):

Luiz Felipe Martins

Ivan Idris

Phuong Vo.T.H

Martin Czygan

Magnus Vilhelm Persson

+1 more

View More author details

Table of Contents (6) Chapters

Preface

1. Module 1

2. Module 2 FREE CHAPTER

3. Module 3

A. Bibliography

Index

Chapter 11. Analyzing Images

In this chapter, we will cover the following recipes:

Setting up OpenCV
Applying Scale-Invariant Feature Transform (SIFT)
Detecting features with SURF
Quantizing colors
Denoising images
Extracting patches from an image
Detecting faces with Haar cascades
Searching for bright stars
Extracting metadata from images
Extracting texture features from images
Applying hierarchical clustering on images
Segmenting images with spectral clustering

Introduction

Image processing is a very large field of study. The techniques used for image processing can often (with small changes) be applied to video analysis as well. We can view image processing as a special type of signal processing. Signal processing is covered in Chapter 6, Signal Processing and Timeseries. However, images pose special challenges, such as high dimensionality (we can define each image pixel to be a feature) and spatial dependence (pixel location matters).

The human visual system is very advanced compared to...

You have been reading a chapter from

Python: End-to-end Data Analysis

Published in: May 2017

Publisher: Packt

ISBN-13: 9781788394697

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Authors (5)

Magnus Vilhelm Persson

Magnus Vilhelm Persson

Magnus Vilhelm Persson is a scientist with a passion for Python and open source software usage and development. He obtained his PhD in Physics/Astronomy from Copenhagen Universitys Centre for Star and Planet Formation (StarPlan) in 2013. Since then, he has continued his research in Astronomy at various academic institutes across Europe. In his research, he uses various types of data and analysis to gain insights into how stars are formed. He has participated in radio shows about Astronomy and also organized workshops and intensive courses about the use of Python for data analysis. You can check out his web page at http://vilhelm.nu.

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Phuong Vo.T.H

Phuong Vo.T.H

Phuong Vo.T.H has a MSc degree in computer science, which is related to machine learning. After graduation, she continued to work in some companies as a data scientist. She has experience in analyzing users' behavior and building recommendation systems based on users' web histories. She loves to read machine learning and mathematics algorithm books, as well as data analysis articles.

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Martin Czygan

Martin Czygan

Martin Czygan studied German literature and computer science in Leipzig, Germany. He has been working as a software engineer for more than 10 years. For the past eight years, he has been diving into Python, and is still enjoying it. In recent years, he has been helping clients to build data processing pipelines and search and analytics systems.

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Luiz Felipe Martins

Luiz Felipe Martins

Luiz Felipe Martins holds a PhD in applied mathematics from Brown University and has worked as a researcher and educator for more than 20 years. His research is mainly in the field of applied probability. He has been involved in developing code for the open source homework system, WeBWorK, where he wrote a library for the visualization of systems of differential equations. He was supported by an NSF grant for this project. Currently, he is an Associate Professor in the Department of Mathematics at Cleveland State University, Cleveland, Ohio, where he has developed several courses in applied mathematics and scientific computing. His current duties include coordinating all first-year calculus sessions.

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Ivan Idris

Ivan Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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