• Hrishikesh Jadhav
• Pushkar Dounde
• Akash Pawar
• Abhishek Muthange

Pervasive sign language is used relatively within our society, deaf and other verbally challenged communication of people with hearing impairments is of prime importance in our society. This paper presents a solution for this purpose. We developed an android application which integrates both computer vision techniques involving Histogram of Oriented Gradients (HOG) as well as Machine Learning techniques such as Convolutional Neural Network (CNN) and Multiclass Support Vector Machine (SVM) to detect and recognize gestures automatically. People tend to face difficulty in communicating on daily basis. Because of that development of assistive, cost-effective, as well as non-invasive technologies to aid the people in need is necessity.

Sign Language, Hand Gesture Recognition, Image Processing, Grey Scale image, Convolution Neural Network

"A Deep Learning Mobile Application based Sign Language Recognition for Aphasic Person", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.d570-d575, May-2021, Available :http://www.jetir.org/papers/JETIR2105465.pdf

"A Deep Learning Mobile Application based Sign Language Recognition for Aphasic Person", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppd570-d575, May-2021, Available at : http://www.jetir.org/papers/JETIR2105465.pdf