Sign Language Recognition using PCA and Hu-Moment Features
Jamal Khan, Sikandar Zulqarnain Khan, Muhammad Omer Bin Saeed, Sami Ullah, Naveed Iqbal, Madiha Sher, Khurram Karim Qureshi · 2024
The deaf community commonly uses sign language for communication, a highly flexible way of conveying messages. Sign language involves a limited number of core concepts and assigned gestures. This paper aims to create a sign language system that will enhance communication within the deaf community. The focus is to implement a software model for sign language recognition using a classifier. The approach involves recognizing and analyzing gestures using principal component analysis features and Hu-Moment features. Several classifiers are utilized to measure accuracy and performance.