Python And Opencv For Sign Language Recognition

Hearing-impaired people cannot communicate with normal people easily. Most people are not aware of sign language recognition. To support this, machine learning and CV can be used to create an impact on the impaired. This can be improved into automatic editors, in which the person can easily understand the sign language of the impaired people by just using hand sign recognition. In non-verbal communication, hand gesture always being an important mode of communication and it plays a vital role to bridge gap between deaf and dumb people. Several sign language recognition systems have been developed but the systems are not flexible and cost-effective. Physically challenged people can express their emotions and feelings through sign language. In this paper, we develop a sign detector that can detect signs and numbers and also other signs that are used in sign language with the help of OpenCV and Keras modules in python. By using this technology, we can understand what they want to convey through sign language which is not a common language to communicate with people. OpenCV and Keras of python are the modules used to achieve our work and the proposed work proved to be a user-friendly approach to communication by using Python language to recognize sign languages for hearing-impaired persons.