Certain Investigations in Hand Gesture Recognition - a Survey

EasyChair Preprint no. 9680

Abstract

As per to the world health organization, 466 million people, or 5% of the world's population, are either deaf, mute, or have hearing loss that prevents them from hearing. Discrimination against disabled individuals and regular people is pervasive. We converse to exchange opinions, but for someone who is paralyzed, especially someone who is deaf or dumb, it can be difficult. A true form of disability is considered to be speech impediment. The only available communication tools for such people are Braille or sign language. In sign language, hand gestures are employed as a means of communication. However, it can be difficult for them to engage with others because the majority of individuals are not conversant in sign language. Since the dawn of time, hand gestures have been an integral aspect of communication. A type Of Visual Communication, sign language is Based on Hand gestures.Therefore want to bridge the  developing Communication tools, a Deaf/Mute person can communicate with other technology that acts as a go-between for the two.The Concept is put into practice using neural network and image Processing concepts. we suggest eliminating the uncertainty that was created into the results by adding background variation.

Keyphrases: CNN, deep learning, gesture recognition, image processing, Sign language interpretation and machine learning

@Booklet{EasyChair:9680,
  author = {M Madhushree and Pravinth Raja and Sin Thuja},
  title = {Certain Investigations in Hand Gesture    Recognition - a Survey},
  howpublished = {EasyChair Preprint no. 9680},

  year = {EasyChair, 2023}}