Real-time Sign Language Recognition using Computer Vision

Abstract

Speech impairment is a disability that affects an individual’s ability to verbal communication. To overcome this issue sign language is used which is one of the most organised languages. There is definitely a need for a method or an application that can recognize sign language gestures so that communication is possible even if someone does not understand sign language. My paper is an effort towards filling the gap between differently-abled people like deaf and dumb and the other people. Image processing combined with machine learning helped in forming a real-time system. Image processing is used for pre-processing the images and extracting different hand from the background. These images obtained after extracting background were used for forming data that contained 24 alphabets of the English language. The Convolutional Neural Network proposed here is tested on both a custom-made dataset and also with real-time hand gestures performed by people of different skin tones. The accuracy obtained by the proposed algorithm is 83%.