ML model to assist people with vision impairment. Using supervised learinng the model is build and trained on.
Problem Statement-
People face difficulties in communication with the people who are deaf and dumb.
The sign used for communication is not recognizable by everyone.
The sign language recognition model can be used to bridge the communication gap.
Simple hand gestures will be used to feed the data set and to train the model in order to recognize different hand gesture easily in future.
Proposed Methodology-
Here, we use python and open cv to create and train a model which will be used for implementing sign language recognition.
Count of numbers from 1-10 using hand gestures will be fed as initial data set.
With that data the model will be trained and validated with new set of data input.
The output will be the exact count of numbers represented using hand gestures in word format.
For example:- V will give the output as 2.