INDIAN SIGN LANGUAGE SYMBOL DETECTION AND RECOGNITION USING DEEP LEARNING TECHNIQUES

Abstract

It is always a huge problem to communicate with someone who has a hearing impairment. The problems in character categorization in Indian Sign Language (ISL) are the focus of the study reported in this article. Those who are deaf or hard of hearing cannot fully communicate by sign language alone. If you've never learned this language, you could find the disabled person's gestures confusing or disorganised. It is important for communication to be reciprocal. We provide an Indian Sign Language-based sign language recognition system in this article. For this analysis to work, the user's webcam must be able to record hand motions, and the system's prediction and display of the image's name are essential. A number of computer vision methods, including grayscale conversion, dilatation, and mask operation, are used to the collected picture throughout the processing phases. Our model is trained and the photographs are identified using a Convolutional Neural Network (CNN).