Author: Jerome A Shaju

Contours in OpenCV represent the boundaries of objects in images and are a fundamental concept in computer vision for shape analysis, object detection, and recognition. Essentially, contours are continuous curves that outline the shape of an object by connecting points along its boundary. They are extracted through a series of image processing operations such as… Continue reading Understanding of Contours in OpenCV

Object tracking in OpenCV is a fundamental technique used in computer vision to monitor and follow the movement of objects within a video stream or sequence of images. It plays a crucial role in various applications such as surveillance, automotive safety systems, human-computer interaction, and augmented reality. At its core, object tracking involves locating a… Continue reading Object Tracking in OpenCV

The HSV color space, often called HSC (Hue, Saturation, and Value), represents colors in terms of their hue, saturation, and value. It’s a transformation of the RGB color space that aims to better represent human perception of color. Let’s break down each component and discuss its relevance in image processing tasks:  Hue (H):  Hue represents… Continue reading Introduction to the HSV Color Space

Handling mouse clicks in OpenCV enables interactive applications where users can interact with images or video frames. By capturing mouse events, such as clicks or movements, developers can implement functionalities like selecting regions of interest (ROIs), annotating images, or triggering specific actions based on user input. This capability adds an interactive dimension to computer vision… Continue reading Handling Mouse Clicks in OpenCV