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Top Image Processing Libraries in Python

Top Image Processing Libraries in Python

Python is a very famous language to learn. It is the fastest growing language in terms and libraries, applications that can be used in machine learning, Artificial intelligence, web development, and many other things which python has covered. With the rise of Data Science i.e. machine learning and artificial intelligence, it has come into the limelight. It is famous for its simple programming syntax, code readability which makes it more productive and easier.

In this article we will discuss about various Image Processing Libraries in Python. Today Image and Video processing techniques are being widely used. Most recently, Indian railways will use facial recognition to fight criminals. Before going towards the libraries lets first discuss how the computer reads image and process it so that it will be easier for you to know the working each of the library.


How Computers Read Images?


Computers read the image in the form of a matrix range between 0 to 255. For colored image, there are 3 channels Red, Green, Blue and there is a matrix associated with each of the channel, each element of this matrix represents the intensity of brightness of that pixel. All the 3 channels will have their separate matrix which is stacked on each other to create 3-D metrics. For Gray/black image there is a 2-D matrix.


Colored Image has 3 channels

Gray/Black scale image has 1 channel.


In the same way, the computer captures video. Video is multiple images/frames which are displayed very quickly.


Now lets move towards various Image Processing Libraries.

  1. OpenCv

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. This library mainly aims at real-time computer vision. In other words, we can say it is a library used for Image Processing. It is mainly used to do all the operations related to Images like to analyze the data from the Camera of an Embedded system or your computer or anything that captures images (e.g. From a LIDAR). It is written in C++ and supported by various programming languages such as C++, Java, Python. Some applications of OpenCV includes read and write Images, detection of faces and its features, text recognition in images, developing augmented reality apps.


  1. Scikit-image

Scikit-Image is an open source python library that uses NumPy arrays as image objects by transforming the original pictures. It converts original image into Numpy array. It is written in C which makes it fast. It has many algorithms for feature detection, image segmentation, color manipulation, filtration and many more. It is often use to utilize grey scale technique for conversion of each pixel into greyscale.


  1. NumPy

NumPy is one of the most important and widely used library in python. It provides support for large, multi-dimensional arrays. As computer reads image as array of data points. Using NumPy we can show image as multi-dimensional array. So by using Numpy basic function such as indexing, slicing, masking we can process the image by modifying the pixel values. It can be used to quickly perform numerical analysis on image.


  1. Pillow

This library is the new version of PIL library which stands for Python Imaging Library. PIL library is used for opening, manipulating, and saving many different image file formats. However, Pillow is the advanced version of PIL which contains basic image operations like resize, converting the image to other formats like jpeg, png, etc.


  1. Matplotlib

Matplotlib is a plotting library for python which is mostly used for 2-D visualizations. This library can be used for altering images to extract information out of it.

So far we have seen few mostly used python libraries but there are various other are also available. Hope you will find it useful.

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