Python Scikit-image | Image Processing Using Scikit-Image
The world is defined with images and, every image has its different specialties. An image can contain much-needed information that can be helpful in various ways.
The process by which we can obtain the information of an image is known as Image Processing.
In today’s scenario, Image processing has a broad range of applications in various fields. Image processing enables us to manipulate and transform lots of images at a single time to obtain useful information from them.
For image processing, One of the popularly utilized programming languages is Python. Python includes very effective libraries and tools which help in obtaining the information of images in image processing.
The most popular image processing libraries used are:
OpenCV, Python Imaging Library (PIL)/Pillow, Scikit-image, Numpy, Mahotas.
Python Scikit-image
scikit-image is a Python package that is assigned for image processing in Python and it uses NumPy arrays. For image processing, it is a set of algorithms.
scikit-image is used for various image processing tasks and it also works with Numpy and SciPy in Python image processing.
Here, we will discuss various useful techniques for image processing using scikit-image.
Features of scikit-image
- It is a very simple and light image processing tool.
- it is built above NumPy, matplotlib and, SciPy.
- Everyone can access and reuse it.
- It is open-source and industrially usable — BSD license.
Installing scikit-image
We have to install Numpy and SciPy before installing scikit-image. it can be easily installed using pip.
Syntax:
pip install –U scikit-image
Reading Images
Importing images in Python using skimage is the very first step in image processing using scikit-image.
The image is stored in form of numbers when it is read using scikit-image. The numbers are defined as pixels and also intensity of the image is defined by using these numbers.
