The Performance of Face Recognition Using the Combination of Viola-Jones, Local Binary Pattern Histogram and Euclidean Distance
Author(s) : Suherwin | Zahir Zainuddin | Amil Ahmad Ilham
International Conference on Informatics and Computational Sciences (ICICoS)/Added to IEEE Xplore: 24 December 2020
Achieving low recognition time and high accuracy in real-time face recognition is challenging. This study implements Viola-Jones, Local Binary Pattern Histogram, and Euclidean Distance for real-time face recognition and calculates the face detection time. The face image is detected using the Viola-Jones method; its features are extracted using the Local Binary Pattern Histogram, and the face is recognized using Euclidean Distance. This study processes sample images from 1013 students as training data, with 20 images represent each student. The experiments show that 268 of 342 testing data are recognized correctly, resulting in an accuracy of 78.4%, with average real-time recognition time of 0.93 seconds.
Keyword(s): Face Detection, Viola-Jones, Face Recognition, Local Binary Pattern Histogram, Euclidean Distance
Year: 2020