Book Image

NumPy Cookbook

Book Image

NumPy Cookbook

Overview of this book

Today's world of science and technology is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy will give you both speed and high productivity. "NumPy Cookbook" will teach you all about NumPy, a leading scientific computing library. NumPy replaces a lot of the functionality of Matlab and Mathematica, but in contrast to those products, it is free and open source. "Numpy Cookbook" will teach you to write readable, efficient, and fast code that is as close to the language of Mathematics as much as possible with the cutting edge open source NumPy software library. You will learn about installing and using NumPy and related concepts. At the end of the book, we will explore related scientific computing projects. This book will give you a solid foundation in NumPy arrays and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project through examples. "NumPy Cookbook" will help you to be productive with NumPy and write clean and fast code.
Table of Contents (17 chapters)
NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Edge detection with the Sobel filter


The Sobel operator (for more information on Sobel operator visit http://en.wikipedia.org/wiki/Sobel_operator) can be used for edge detection in images. The edge detection is based on performing a discrete differentiation on the image intensity. Because an image is two-dimensional, the gradient also has two components; unless we limit ourselves to one dimension, of course. We will apply the Sobel filter to the picture of Lena Soderberg.

How to do it...

In this section, we will learn how to apply the Sobel filter to detect edges in the Lena image.

  1. Apply the Sobel filter in the x direction.

    To apply the Sobel filter in the x direction, we need to set the axis parameter to 0:

    sobelx = scipy.ndimage.sobel(lena, axis=0, mode='constant')
  2. Apply the Sobel filter in the y direction.

    To apply the Sobel filter in the y direction, we need to set the axis parameter to 1:

    sobely = scipy.ndimage.sobel(lena, axis=1, mode='constant')
  3. Apply the default Sobel filter.

    The default...