Development of sign language detection and identification based on python

Azman, Nur Iffah Maisarah (2025) Development of sign language detection and identification based on python. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Speech is the world's primary form of communication. However, deaf or hard-of-hearing people find it difficult to communicate because they have to use sign language. There is only one method available for their communication and such a common method of communication in gesture is sign language. Sign language is a form of communication used by hearing-impaired communities. This project aims to develop a system for hearing and deaf people to communicate more easily by developing a system that turns sign language into text. This project focuses on creating an automated sign language recognition system using Python to improve communication. The system combines hand landmark detection with a random forest classifier to recognize and interpret American Sign Language (ASL) gestures. Using a dataset of ASL gestures, the model was trained on 80% of the data and tested on 20%, achieving 97.01% accuracy. To solve this gap, this study develops to make sign language easier to communicate with other people.

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