Learn to apply different geometric transformations to images like rotation, translation etc.

November 11, 2025 - Learn key image-processing techniques with OpenCV. Basic to advanced. Resizing, edge detection, contour finding, morphological operations, more.

The imgproc module in OpenCV is a collection of per-pixel image operations (color conversions, filters) drawing (contours, objects, text), and geometry transformations (warping, resize) useful for computer vision. Here's an overview of the content in the imgproc module, categorized for easier ...

Grayscale images contain only intensity information, making processing more efficient. OpenCV provides the `cv2.cvtColor()` function to convert images between different color spaces, including from BGR (used by OpenCV) to grayscale. Blurring and Smoothing Blurring is a crucial technique for ...

September 6, 2024 - This blog will guide you through ... everything from reading and displaying images, converting color spaces, and resizing images, to more advanced tasks like edge detection, contour detection, and thresholding....

OpenCV’s histogram equalization and adaptive histogram equalization are valuable tools for achieving optimal contrast, particularly in scenarios with varying lighting conditions.

July 1, 2021 - It is one of the most important and fundamental techniques in image processing, Cropping is used to get a particular part of an image. To crop an image. You just need the coordinates from an image according to your area of interest. For a complete analysis, check the below code in OpenCV.

In this section you will learn basic operations on image like pixel editing, geometric transformations, code optimization, some mathematical tools etc.

Camera calibration and 3D reconstruction (calib3d module) - extract 3D world information from 2D images

February 22, 2024 - This tutorial demonstrated the ... and displaying images were showcased along with image processing techniques, such as converting images to grayscale and applying edge detection....

Then, we will go on to explore various processing techniques like image enhancement methods, image filtering techniques for edge detection, morphological operations, thresholding techniques, blob detection, and contour detection.

January 17, 2025 - Pre-processing in Computer Vision: Many computer vision algorithms require pre-processed images. Techniques like noise reduction and contrast enhancement from image processing improve the accuracy of computer vision tasks.

This module offers a comprehensive suite of image processing functions, enabling tasks such as those listed above. Generated on Wed Apr 15 2026 04:16:35 for OpenCV by 1.12.0

March 14, 2023 - It is done using techniques such as deconvolution, which is used to get the original image from a blurred version, or denoising, which is used to remove noise from an image. ... Image preprocessing is quite useful to improve the quality of images ...

Let’s take a closer look at some of these algorithms. 👉 Support Vector Machines (SVM) and K-Nearest Neighbors (KNN) algorithms are used in image classification tasks by grouping similar data points. These algorithms are suitable for distinguishing between categories such as animals or objects.

December 20, 2023 - YCrCb: This color space represents an image using its luminance (Y) and two chrominance channels (Cr and Cb). YCrCb is commonly used in video compression and processing. Grayscale: Grayscale is a single-channel color space where pixel values represent the intensity of light. OpenCV allows you to convert images from one color space to another using functions like cv2.cvtColor().

January 6, 2024 - Introduction to Basic Image Processing with OpenCVTable of contentsImport librariesDisplay image directly1. Reading images using OpenCV2. Display image attributes3. Display images using Matplotlib4. Working with color images5.

October 28, 2024 - Therefore, we apply a threshold ... from an image. This works best with binary images, so you should apply a thresholding technique like a Sobel edge....

April 12, 2023 - Explore and run AI code with Kaggle Notebooks | Using data from Cat and Dog