Drawing on screen using P5.js and ml5.js

Author(s)	Mr. Aryan lakhanpal, Mr. Aryan Pandey
Country	India
Abstract	This paper presents a novel approach to creating an interactive drawing application using hand pose detection. The system leverages ML5.js (a machine learning library) and P5.js (a creative coding library) to detect hand gestures in real-time and translate them into drawing actions on a canvas. By tracking the distance between the thumb and other fingers of the user's hand, the system enables the creation of a virtual paintbrush with different colors. Additionally, the system allows users to erase the canvas by joining all fingers of the right hand. The brush size can be dynamically adjusted based on the distance between the forefinger and thumb of the left hand. This project demonstrates the potential of combining machine learning and creative coding for intuitive human-computer interaction.
Keywords	Hand pose detection, ml5.js, p5.js, digital drawing, human-computer interaction, gesture-based interaction, real-time processing.
Field	Computer
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-20

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International Journal For Multidisciplinary Research