A Survey on Sign Language Recognition with Efficient Hand Gesture Representation

Abstract

Image classification is one amongst classical issue of concern in image processing. There are various techniques for solving this issue. Sign languages are natural language that want to communicate with deaf and mute people. There's much different sign language within the world. But the most focused of system is on Sign language (SL) which is on the way of standardization there in the system will focused on hand gestures only. Hand gesture is extremely important a part of the body for exchange ideas, messages, and thoughts among deaf and dumb people. The proposed system will recognize the number 0 to 9 and alphabets from American language. It'll divide into three parts i.e., pre-processing, feature extraction, classification. It'll initially identify the gestures from American Sign language. Finally, the system processes that gesture to recognize number with the assistance of classification using CNN. Additionally, we'll play the speech of that identified alphabets. Keywords: Hybrid Approach, American Sign Language, Number Gesture Recognition. Feature Extraction.