Face Recognition Automated System for Visually Impaired Peoples Using Machine Learning
Kandi Jyothsna, Vivek Kumar, Saroj Shambharkar, Dasari Anantha Reddy, Chandrashekhar N Bhoyar, Rachna K. Somkunwar · 2022
Recent studies and surveys are done by various researchers in the field of Machine Learning and the automation-based system say that the ratio of physically impaired (deaf/dumb) people has been drastically increased due to various health issues in the next generation. Despite of birth defects another reason for this increase in the ratio is an accident, natural health issues, or an oral disease. Victim of these types of health defects faces a lot of problems while communicating with other people in their daily routine life. All physically impaired people use a special language known as sign language to communicate with their colleagues, friend relatives but they are unable to communicate with other people who don’t know sign language. It is all known that communication plays a very important role in everyone’s day-to-day life. To help them, many automatic systems with specialized software have been developed by various researchers and the use of technology is increasing every day. Using the advanced technology, Machine Learning, in our research work, we are trying to design a Vision-based approach that will work by recognizing the face of a user. This approach is based on real-time data, this data is given as input (set of frames of a face from various angles of a physically impaired person) to the system. This set of frames will be processed, and segmented further and its various features will be extracted using a Machine Learning algorithm finally the output of the system is recognized in text format in any vision-based system.