Hand Gesture Recognition for Mute People

Abstract: More than 500 million people of the world suffer from some physical, sensory or mental disability. Often their lives are handicapped by physical and social barriers which hamper their full participation from society and the enjoyment of equal rights and opportunities. Many mute people use sign language. Sign language uses gestures instead of sound to convey meaning, simultaneously combining hand shapes, orientations and movement of the hands, arms or body and facial expressions to express fluidly a speaker’s thoughts. Signs are used to communicate words and sentences to audience. This paper focuses on developing an algorithm for recognition of hand gestures with reasonable accuracy, where the input to the pattern recognition system will be given from the hand. It recognizes the pattern and the display the pattern in the form of the text. The info giving by camera are collected and stored in the database. The exact meaning of the information is matched with the samples stored previously in the database and is printed. The image is processed considering the parameters like the number of fingers used, the angles between them and hsv value of that which is matched with the saturation image and then the information is displayed in the form of text.

Keywords: Hand Gestures, Computer Vision, Sign Languages, Open CV, and Mute people.