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Authors
Gurunandan M G,K C Chandana,Deepika J,Neha Bhatt
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Keywords
Hand Gesture Recognition, Human-Computer Interaction (HCI), OpenCV, Python, Computer Vision (CV), Image Processing (IP), Real-Time Recognition (RTR), Contour Detection (CD), Convex Hull (CH), Feature Extraction (FE), Sign Language Recognition (SLR), Virtual Mouse Control (VMC), Gesture-Based Interfaces (GBI), Machine Vision (MV), Assistive Technology (AT), Pattern Recognition (PR).
Abstract
This paper presents the Hand Gesture Recognition Using OpenCV And Python (HGRUOP), Hand gesture recognition (HGR) is an emerging field in Human-Computer Interaction (HCI) that enables users to communicate with machines through intuitive, touch-free gestures. This project presents a real-time hand gesture recognition system using OpenCV and Python stands [1] the system leverages computer vision techniques such as background subtraction, contour detection, convex hull, and feature extraction to identify and classify gestures made by the human hand. By capturing live video feed through a webcam, the program preprocesses each frame, segments the hand region, and detects finger positions to interpret different gestures.
[2] personalized recommendations, and automating routine tasks.
These recognized gestures can be mapped to specific commands, enabling applications in virtual mouse control, gaming, robotics, and sign language interpretation. The proposed approach emphasizes accuracy, low computational cost, and ease of implementation, making it suitable for real-time applications. [3](keeping the conversation coherent). Overall, the system provides a step toward creating more natural and efficient ways of human-computer interaction (HCI)without the need for additional hardware.
This project demonstrates how OpenCV, combined with Python's simplicity and flexibility, can be effectively used to build vision-based interaction systems. The results highlight the potential of gesture recognition technology in bridging the gap between humans and machines, paving the way for innovative solutions in assistive technology, automation, and immersive user experiences.
IJCRT's Publication Details
Unique Identification Number - IJCRT2509171
Paper ID - 293577
Author type - Indian Author
Page Number(s) - b411-b423
Pubished in - Volume 13 | Issue 9 | September 2025
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No Of Downloads - 25
Author Country - India, 560035, Bangalore, Bangalore, 560035, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Gurunandan M G,K C Chandana,Deepika J,Neha Bhatt, "Hand Gesture Recognition Using OpenCV And Python", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 9, pp.b411-b423, September 2025, Available at :http://www.ijcrt.org/papers/IJCRT2509171.pdf
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