Letters Of Arabic Sign Language Recognition

Arabic Sign Language Recognition – Project Description

The Arabic Sign Language Recognition system is designed to bridge communication gaps by automatically recognizing hand gestures used in sign language. The approach relies on extracting hand keypoints that represent the position and movement of fingers and joints.

For this project, I utilized MediaPipe, a powerful framework for real-time hand tracking, to extract precise keypoints of the hand. These keypoints serve as numerical features that capture the gesture’s structure. Once extracted, the features are passed to a Support Vector Machine (SVM) classifier, which learns to distinguish between different Arabic sign language gestures.

Key points:

️ MediaPipe provides accurate hand landmark detection in real-time.

Extracted keypoints are used as input features for classification.

️ SVM ensures robust recognition of gestures with high accuracy.

Enables practical applications such as communication aids, educational tools, and accessibility solutions.