Computer Vision-Based Hand Gesture Recognition

Hand gesture recognition plays a vital role in bridging communication gaps for individuals with hearing impairments. This abstract explores the application of computer vision and machine learning techniques to give sign language gestures. By analyzing and classifying the intricate movements of hand and finger configurations, these systems facilitate real-time translation of sign language into text or speech. The potential impact on accessibility and inclusivity is substantial, empowering the deaf and hard-ofhearing community to communicate effortlessly with the broader society. This abstract encapsulates the significance of hand gesture recognition in breaking down linguistic barriers and fostering a more inclusive world.