Sign Language Alphabet Detection System
DOI:
https://doi.org/10.37628/ijaic.v9i2.1950Abstract
Currently, gesture recognition for hands and sign language detection for human-computer interaction is
the main emphasis of computer vision and machine learning. The creation of systems that can identify
gestures and use them to transmit data or control devices is one of the main goals. Specifically, hand
gestures entail dynamic hand movements that require explanations in both the spatial and temporal
domains, whereas hand postures reflect the static structure of the hand. The goal of this project is to
develop a vision-based system that can recognise sign language in real time. A vision-based system
makes sense because it allows people to engage with computers in a more direct and organic way. The
investigation of interaction between people and machines through recognition of gestures has
led to the integration of this type of technology throughout multiple fields, given the importance
of the hand of humans as a means of communication in daily life and the ongoing advancement
of the processing of video and images methods. Virtual reality, interactive screens, video game
consoles, medical apps, and sign language recognition are a few of these. While sign language
is a prevalent means of communication for deaf people, there are obstacles when deaf people
interact with hearing people in traditional contexts. The goal of this research is to help address
these issues and promote more seamless interactions between hearing and deaf people.
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