Open AccessHSV Values and OpenCV for Object Tracking
Author(s) -
Mir Mahpara Gulzar,
Ravinder Pal Singh,
Dr Monika Mehra
Publication year - 2022
Publication title -
international journal of innovative research in computer science and technology
Language(s) - English
Resource type - Journals
ISSN - 2347-5552
DOI - 10.55524/ijircst.2022.10.1.8
Subject(s) - computer vision , artificial intelligence , hue , hsl and hsv , computer science , video tracking , tracing , tracking (education) , object (grammar) , computer graphics (images) , psychology , pedagogy , virus , virology , biology , operating system
This research shows how colour and motion may be utilised to speed up the surveillance of things. Video tracing is a technique for detecting a huge vehicle over a long distance using a camera. The main goal of video tracking is to link objects in subsequent video frames. When objects move faster than the frames per second, maintaining connection might be difficult. Using Hue saturation space values and OpenCV in separate video frames, this article shows how to follow moving objects in real-time. We begin by finding the HSV value of the object to be tested, and then we understand the steps along. The tracking of the items was shown to be 90 percent accurate.