Conversion of American Sign Language into Text using Deep Learning .

The Sign language is one of the easy ways of communication to dumb and deaf people. Not all people can understand sign language; the requirement of sign language translator is high. This paper focuses on detecting sign language using deep learning concepts, which acts as a translator. The aim of this project is to convert sign language of static type into its corresponding text. This is done using 2 main steps, data creation and training and deploying the model. The process include real time input which is then converted into threshold image, later these images are trained using CNN model and finally feature classification is done. Then we obtain Static ASL output.