Abstract: Sign language is a good visual communication aid for those with auditory disabilities. This language is also prevalent for those with speech impairment. However, the general populous have little knowledge on sign language, and often find difficulty communicating with someone who is primarily versed in sign language. Our goal is to build a system that can provide robust hand sign-language gesture recognition for SL. This can be of extensive help in public places, especially sign language that isn't often universally understood by the majority of people. This chose four signs used worldwide and prepared a data set for these signs and performed the necessary processing for them, then we chose the SVM algorithm to classify these data, and the algorithm showed a high classification efficiency that reached 99%.
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DOI:
10.17148/IJARCCE.2025.14714
