• M.R.U.Preethika
• Sokitha K
• M.S.Sai Prasanthini
• Dr. J. Arokia Renjith

Recognizing hand gestures from an image has been significant for the future technology into creating new systems and coming up with solutions for advanced level of human and computer interactions. In this work, we have created a system which would aid to the future technology in the human-computer interactions. Our work aids in two ways, one is to provide a sign language interpretation using hand gestures, another is to use gestures in controlling the computer system partially. We have come up with our very own sign language which will be helpful for visual communication with the deaf and mute people. And in this work we have also come up with a novel way of partially controlling a computer screen such as controlling a video, a webpage etc., with the use of hand gesture. This system is vision based and uses machine learning algorithm and inputting the images through a computer web camera. Initially we would get the images through the web camera, then the hand region is extracted using background subtraction, and then fingers are segmented. And finally a rule classifier is applied to detect the hand gesture. We have used OpenCV and MediaPipe.

Hand gesture, machine learning, open cv

"Hand Gesture Recognition Using Haar Cascade Algorithm In Media Pipe For Sign Language And Gesture Control.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.i289-i294, May-2022, Available :http://www.jetir.org/papers/JETIR2205941.pdf

"Hand Gesture Recognition Using Haar Cascade Algorithm In Media Pipe For Sign Language And Gesture Control.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppi289-i294, May-2022, Available at : http://www.jetir.org/papers/JETIR2205941.pdf