HSV Values and OpenCV for Object Tracking

Mir Mahpara Gulzar; Ravinder Pal Singh; Monika Mehra

doi:10.55524/

Authors

Mir Mahpara Gulzar M.Tech, Electronics and Communication Engineering, RIMT University, Punjab, India Author
Ravinder Pal Singh Technical Head, Department of Research, Innovations and Incubation, RIMT University, Punjab, India Author
Monika Mehra Head of Department, Electronics and Communication Engineering, RIMT University, Punjab, India Author

DOI:

https://doi.org/10.55524/

Keywords:

HSV, OpenCV, Object tracking, Video frames, GUI

Abstract

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.

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