#### Overview of this book

Mastering SciPy
Credits
www.PacktPub.com
Preface
Free Chapter
Numerical Linear Algebra
Interpolation and Approximation
Differentiation and Integration
Nonlinear Equations and Optimization
Initial Value Problems for Ordinary Differential Equations
Computational Geometry
Descriptive Statistics
Inference and Data Analysis
Mathematical Imaging
Index

## Image analysis

The aim of this section is the extraction of information from images. We are going to focus on two cases:

• Image structure

• Object recognition

### Image structure

The goal is the representation of the contents of an image using simple structures. We focus on one case alone: image segmentation. We encourage the reader to explore other settings, such as `quadtree` decompositions.

Segmentation is a method to represent an image by partition into multiple objects (segments); each of them sharing some common property.

In the case of binary images, we can accomplish this by a process of labeling, as we have shown in a previous section. Let's revisit that technique with an artificial image composed by 30 random disks placed on a 64 x 64 canvas:

```In [1]: import numpy as np, matplotlib.pyplot as plt
In [2]: from skimage.draw import circle
In [3]: image = np.zeros((64, 64)).astype('bool')
In [4]: for k in range(30):
...:     x0, y0 = np.random.randint(64, size=(2))
...:     image[circle(x0, y0...```