Development of sign language interpreter using computer vision technique

Zainal, Nasha Athilah (2022) Development of sign language interpreter using computer vision technique. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

To assist the social interaction of deaf and hearing impaired people, efficient interactive communication tools are expected. Gesture recognition forms the basis for translating sign languages where gesture recognition plays a critical role in Sign Language Recognition (SLR). The purpose of this project is to provide a sign language interpreter to ease the interaction with the hearing-impaired person based on the computer vision approach. The dataset from the website Roboflow Universe will be used which consists of 26 different hand sign gestures which include A-Z alphabet gestures. All the labeled images will be set as a training set. For the test set, the Python OpenCV library will be used to capture sign gestures from the computer’s webcam. The training and test set images will be compared and classified based on the Support Vector Machine (SVM). The output of the system will predict the accuracy of the hand gesture captured by the webcam.

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