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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM28838

VIRTUAL PAINT

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM28838

Volume:

8 |

2 |

Feb 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM28838

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

YP

Yash Phadatare

SK

Sanju Khetawat

NM

Niyati Manerikar

HB

Harshren Bachhav

PB

Priyadarshini Badgujar

PPB

Prof. Priyadarshini Badgujar

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Abstract

The Virtual Painting system introduces an exciting new way to create digital art by combining artificial intelligence with real-time hand gesture recognition. Developed in Python, the system uses a webcam to capture live video, translating simple hand movements into drawing commands on a virtual canvas. By eliminating the need for traditional input tools like a mouse, stylus, or touchscreen, it allows users to draw freely with just their hands. This touch-free interaction not only makes digital art more accessible to a broader audience but also opens up new possibilities for creative expression. At the core of the system are advanced computer vision technologies and widely-used open- source libraries such as OpenCV, Mediapipe, and NumPy. Mediapipe is particularly important, offering a highly accurate hand detection model that can track 21 distinct landmarks on the hand in real time. This precise tracking enables users to control the application through intuitive gestures—selecting drawing tools, switching modes, erasing, clearing the canvas, and more. Whether drawing freehand or creating geometric shapes like circles, rectangles, and ellipses, the system provides a flexible and responsive platform for various artistic needs. Ultimately, this project showcases how the fusion of AI and gesture control can reshape the way we interact with digital spaces, making technology not only more functional but also more human-centered and creatively empowering.

KEYWORDS

Python Artificial Intelligence Virtual Painting Hand Gesture Recognition OpenCV Media pipe NumPy Canvas Hand Tracking Gesture Recognition.

Cite This Article

Yash Phadatare, Sanju Khetawat, Niyati Manerikar, Harshren Bachhav, Priyadarshini Badgujar, Prof. Priyadarshini Badgujar, "VIRTUAL PAINT," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 2, Feb 2024. https://doi.org/10.55041/IJSREM28838

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Publication Date

12/31/45798

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Double-Blind Peer Review

Review Rounds: 2

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