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Last updated: Feb 25, 2022

Image Processing Basics

Images, like data, must be processed before they can be used in computer vision processes, in the same way that data must be analysed and preprocessed before it can be used in machine learning. This aids in the extraction of every pixel of an image with greater clarity and accuracy using algorithms such as edge detection and the Image Pyramid method.
Digital Image Processing EASY
This blog focuses on how the image is represented by a computer and Digital image processing.
OpenCV cv2.threshold() Function MEDIUM
In this article, we will learn about the OpenCV cv2.threshold() function. We will explore simple thresholding and adaptive thresholding in this article.
Digital Image Processing
In this article, we will learn about digital image processing. We will learn about image and image processing and discuss digital image processing in detail.
Morphological Operations in Image Processing EASY
In this blog, we will learn about Morphological Operations in Image Processing. We will learn about its types, implementation, and much more for better understanding.
Seamless Cloning in Image Processing MEDIUM
In this article, we will learn about Seamless Cloning in Image Processing, its types, and its implementation in openCV and its applications.
Edge Detection EASY
This blog will provide a theoretical introduction to Edge Detection and its various techniques.
Image Pyramids EASY
 This blog will provide a theoretical introduction to the Image Pyramid and its various types.
Scale-Invariant Feature Transform (SIFT) EASY
This article focuses on the concept and math behind SIFT
Speeded Up Robust Features (SURF) EASY
In this article, we will see the basics of SURF and a brief about the feature extraction and description.
Local Binary Pattern Algorithm EASY
This article aims to understand the Local Binary Pattern Algorithm.
Difference between Dilation and Erosion MEDIUM
This article briefly discusses the difference between morphological operations, dilation and erosion in detail.