Hand Sign Recognition using Machine Learning

Hand sign recognition is an emerging and impactful application in the field of human-computer interaction (HCI) and assistive technologies, particularly for communication with and among hearing- and speech-impaired individuals. This project aims to develop an efficient and accurate system capable of recognizing hand gestures representing specific signs or alphabets using various computer vision and machine learning techniques. The proposed system processes hand signs captured through a live camera or image input and classifies them using robust algorithms to interpret the meaning of each gesture. The system incorporates a combination of image processing techniques and machine learning models. Initially, the hand region is isolated from the background using methods such as colour segmentation or background subtraction.