International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 10 Issue: 02 | Feb 2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 719 Virtual Mouse Control Using Hand Gesture Recognition G N Srinivas 1 , S Sanjay Pratap 2 , V S Subrahmanyam 3 , K G Nagapriya 4 , A Venkata Srinivasa Rao 5 5 Department of ECE, Sasi Institute of Technology & Engineering, Tadepalligudem, W.G.Dist, India. 1,2,3,4 UG Students, Department of ECE, Sasi Institute of Technology & Engineering, Tadepalligudem, W.G.Dist, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The mouse is an excellent device for human- computer interaction. We currently use three types of mice: wired, wireless, and Bluetooth. We need power to connect a dongle to a PC in all of these scenarios. This work employs cutting-edge machine learning and computer vision algorithms to recognize hand gestures, which work flawlessly without the use of any hardware. It is compatible with CNN models implemented by mediapipe. In this paper, we work on S.Shriram’s algorithm that [11] propose a method for controlling the cursor's location using only one's hands and no mouse. Some actions, like clicking and dragging items, will necessitate a variety of hand movements. The proposed system will only require the use of a single computer. A camera is used as an input device. The following programs will be used: The proposed system necessitates the use of Python and OpenCV. The output of the camera will be displayed on the system's display so that the end-user can fine-tune it. Key Words: Camera, Machine Learning, CNN Model, Mediapipe, Virtual Mouse, etc 1. INTRODUCTION Hand gestures are universally recognized as the most expressive and effective form of human communication. Hand signals, thumbs up, and thumbs down have always existed. Gestures are regarded as the most natural way for people to communicate with one another. It has a lot of personality. It was written in such a way that it could be understood by the deaf and dumb. So why not put it to use on our machines? In this work, we present actual hand gestures. The initial setup includes a low-cost USB web camera for system input. This paper proposes a real-time hand gesture system. The experimental setup of the system makes use of a low-cost web camera with high-definition recording capability that is installed in a fixed position. A camera mounted on a computer monitor is used to photograph a laptop. This project proposes an effective hand gesture segmentation technique based on pre-processing, background subtraction, and edge detection approaches. The Python programming language and OpenCV, a computer vision library, were used to create the AI virtual mouse system. The MediaPipe package is used to track hands and fingers, as well as the Pynput, Autopy, and PyAutoGUI packages for navigating the computer's window screen and performing operations like left click, right click, and scrolling. 2. LITERATURE SURVEY Chen-Chiung Hsieh et al. [1] proposed "A Real Time Hand Gesture Recognition System Using Motion History Image" to control the mouse cursor. The proposed method employs an adaptive skin colour detection model to reduce misclassifications. To develop these methodologies, they used a C++ software platform with the image processing library open cv installed. Kamran Niyazi et al [2] proposed "Mouse Simulation Using Two Colored Tapes," which used the Background Subtraction method, Skin Detection method, and HSV Color Model to control the cursor and perform clicking operations. The distance between the tape colours was used to guide the clicking operations. This model was created using Java software. Abhik Banerjee et al. [3] proposed a "Mouse Control Using a Web Camera Based on Color Detection" to control cursor movements and click events by detecting camera colour. Each colour represents a different cursor control, and clicking actions are performed by simultaneously detecting the colours. This method was created with the help of MATLAB software and the MATLAB image processing tool box. "Vision-based Computer Mouse Control Using Hand Gestures" [4] was proposed by Sandeep Thakur et al. To improve the efficiency and reliability of the interaction, this method employs a vision-based system to control various mouse activities such as left and right clicking with hand gestures. To improve the system's efficiency and performance, different colour caps are used on fingers to recognise hand gestures. The MATLAB environment was used to implement this method. To control the mouse cursor, Horatiu-stefan Grif et al [5] proposed "Mouse Cursor Control Based on Hand Gesture". They used an external camera attached to a hand pad and colour strips attached to the fingers in the proposed method. To implement this methodology, they used C programming software along with an image processing library called OpenCV. Pooja Kumari et al. [6] proposed "Cursor Control Using Hand Gestures" for controlling a mouse with camera- captured hand gestures. The camera acts as a sensor in this method, capturing and recognising colour tips attached to the hand. Because it requires the user to have colour tips on his hand in order to control the mouse, this method is also known as the marker-based approach method. To implement this methodology, they used the MATLAB environment, the MATLAB Image Processing Tool box, and