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Thresholding — a Way to Make Images More Visible (CV-04)

Extract More Information from Images with Thresholding

Md. Zubair
Towards Data Science
7 min readApr 26, 2023

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Image by Jonas Svidras from Pixabay

Motivation

In the real world, we aren’t always dealing with a 100% clear image. Sometimes, the image gets blurred, distorted, and so on. It becomes a crucial issue to extract information from these types of images. That is why transparent, clear, and more eye-catching images play a vital role in getting comprehensive information.

The left side image is taken from the pxfuel under creative common license. The right-side image is generated after applying thresholding.

The image after thresholding is more visually clear. Apart from the image, this thresholding technique might be helpful in thousands of use cases. If you read the article till the end, you will be a master of how to use, where to use, and when to use image thresholding in real life.

In detail, image thresholding transforms an image into a binary image to extract more information.

Table of Contents

  1. What is Image Thresholding?
  2. Difference Between Global and Local Thresholding
  3. Popular Thresholding Techniques and Python Implementation

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Towards Data Science
Towards Data Science

Published in Towards Data Science

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Md. Zubair
Md. Zubair

Written by Md. Zubair

I'm a Ph.D. in CS Student, like to write a series of articles on Data Science Guidelines. For Contact - https://www.linkedin.com/in/zubair063/

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