Air Canvas, often referred to as the Virtual Pen, is a cutting-edge project leveraging the power of OpenCV and computer vision technology. Its primary aim is to transform any ordinary surface into an engaging and interactive sketching area, redefining the way we create digital art and design.

1. Centre of Competence
in
Visual Computing
Internship Phase II presentation
Air Canvas - A Virtual Pen
Under the Guidance of
Prof Dr Soumya A
Team Members: Akshaya Kumar (1RV20EC014), Charan Kumar M N
(1RV21EC404 ) Pradeep K R (1RV19EC125) and Tabrez Ahmed(1RV20EC167)

2. Introduction
● Air Canvas, often referred to as the Virtual Pen, is a cutting-edge project
leveraging the power of OpenCV and computer vision technology. Its primary
aim is to transform any ordinary surface into an engaging and interactive
sketching area, redefining the way we create digital art and design.
● One of the core features of this project involves the implementation of
sophisticated color recognition and tracking methods. These techniques allow
users to wield a "virtual pen" and create digital masterpieces by simply moving
a colored object in their hands. It offers a remarkably immersive experience
that closely emulates the sensation of painting, all made possible through the
fusion of technology and creativity.

3. Literature Review- Summary
Application of Computer Vision and Deep Learning: The literature review highlights the widespread application
of computer vision and deep learning algorithms, such as RCNN, Faster-RCNN and SSD, in various projects
related to object detection, tracking, and interactive systems. These technologies are extensively used for
real-time image and video processing.
Virtual Drawing and Gesture Recognition: The review showcases a recurring theme of virtual drawing and
gesture recognition systems that allow users to draw or write in the air using colored markers, styluses, or
hand gestures. OpenCV and similar technologies are consistently used to track the movement of objects or
fingertips in real-time, providing interactive and immersive experiences.
Addressing Societal and Educational Challenges: Several research papers focus on addressing societal issues,
such as paper wastage, smartphone dependence, and communication challenges. They propose innovative
solutions that utilize computer vision and deep learning to create cost-effective and eco-friendly
alternatives, particularly in the fields of education and communication. These projects demonstrate the
potential of technology to offer solutions to real-world problems.

4. Problem Statement
The problem statement for this project is to create an innovative and cost-effective virtual hand gesture
painting system that enables users to draw shapes and text in a digital environment using hand
gestures. The challenge is to design a system that accurately recognizes and translates these gestures
into digital strokes on a virtual canvas, allowing for an intuitive and immersive drawing experience. This
project aims to overcome the limitations of traditional input devices and provide an interactive platform
for creative expression, making digital art more accessible and engaging for a wide range of users,
regardless of their technical expertise or familiarity with specialized tools.

5. Engineering Knowledge
Profound understanding of image processing techniques and practical applications, enabling
manipulation, analysis, and interpretation of visual data.
Comprehensive knowledge of machine learning concepts, including the design and
implementation of various algorithms for tasks such as classification, regression, and object
detection.
Practical experience with tools like OpenCV and exploration of neural networks, particularly
Convolutional Neural Networks (CNNs), in the context of computer vision.
Enhanced interdisciplinary collaboration, communication, and ethical responsibility within
engineering practice, emphasizing the integration of technical and professional competencies.

6. Resource Management
Team Task Division:
Tabrez Ahmed: Project initiation, technology stack selection, and OpenCV integration.
Akshaya Kumar: UI design and graphical user interface development.
Charan Kumar M N: Color detection and tracking algorithm optimization.
Pradeep K R: Drawing points storage and canvas interaction.
Resources:
Hardware: Personal computers with webcams.
Software: Python, OpenCV, NumPy, Git/GitHub for collaboration.

7. Environment and Sustainability
Environment & Sustainability:
Paperless Art: The Air Canvas project reduces paper usage by offering a digital canvas for drawing and
painting, minimizing the environmental impact of traditional art supplies.
Eco-Friendly: By eliminating the use of toxic chemicals, it promotes eco-friendliness in artistic
endeavors.
Reduced Electronic Waste: Utilizing existing hardware minimizes the need for extra electronic devices,
contributing to electronic waste reduction.
Societal Importance:
Educational Tool: The Air Canvas is valuable in educational settings, offering an eco-friendly tool for
teaching and creativity.
Therapeutic Benefits: It serves as a therapeutic tool, enhancing societal well-being and inclusivity,
especially for individuals with specific needs.

8. Data Preprocessing
Color Space Conversion: The frames captured by the webcam are converted from the RGB color
space to the HSV color space. This conversion simplifies color detection and tracking.
Thresholding: The upper and lower HSV values are set using trackbars to define the range of
colors to be detected. This thresholding helps in identifying the colored marker used for
drawing.
Morphological Operations: Erosion and dilation operations are applied to the mask obtained
after thresholding. Erosion reduces impurities, while dilation restores the eroded mask. These
operations help in improving color detection accuracy.
Contour Detection: Contours of the detected colored marker are found using OpenCV's contour
detection functions. This allows for the identification of the marker's position and motion.
Handling Missing Data: Deque structures are used to store the coordinates of drawing points.
When no motion is detected, new deques are appended to avoid errors and ensure a smooth
drawing experience.

9. References
1.S Guennouni, A Ahaitouf and A Mansouriss , ―Multiple object detection using Open CV on an embedded platform‖, 2014 Third IEEE International
Colloquium in Information Science and Technology (CIST), 2014, pp. 374-377.
2.Chandan, Mohana A.H Jain ―The Real Time Object Detection and Tracking Using Deep Learning and OpenCV‖, 2018 International Conference
on Inventive Research in Computing Applications (ICIRCA), 2018, pp. 1305-1308.
3.Y. Huang, X. Liu, X. Zhang, and L. Jin, "A Pointing Gesture Based Egocentric Interaction System: Dataset, Approach, and Application," 2016 IEEE
Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, NV, pp. 370-377, 2016.
.4.P. Ramasamy, G. Prabhu, and R. Srinivasan, "An economical air writing system is converting finger movements to text using a web camera," 2016
International Conference on Recent Trends in Information Technology (ICRTIT), Chennai, pp. 1-6, 2016.
5.Fan Zhang, Valentin Bazarevsky, Andrey Vakunov, Andrei Tkachenka, George Sung, Chuo-Ling Chang, et al., "MediaPipe Hands: On-device Real-
time Hand Tracking", 18, June 2020.
6.PavithraRamasamy, Prabhu. G, Dr. R. Srinivasan, “ An Economical Air Writing System Converting Finger Movements To Text Using Web Camera” in
Fifth International Conference on Recent Trends in Information Technology, 978-1-4673- 9802-2, 2016.
7.Prof. S.U. Saoji, NishthaDua, Akash Kumar Choudhary, Bharat Phogat, “ Air canvas application using OpenCV and numpy in python” in IRJET,
(Deemed to be University) College of Engineering, Pune, Volume: 08 Issue: 08, e-ISSN: 2395-0056, p-ISSN: 2395-0072, Aug 2021.
8.D. Vijendra Kumar, G.Vijaya Raj Siddarth, R. Venkata Satya Sravani, I.VishnuVardhan Reddy, Y. Lalitha Sri Naga DurgaVyshnavi, “Building a Air
Canvas using Numpy and Opencv in Python” in IJMTST, Godavari Institute of Engineering and Technology(A), JNTUK, Kakinada, ISSN: 2455-3778,
DOI: https://doi.org/10.46501/IJMTST08S0528, 2022

10. Thank You