@inproceedings{d5972e8d1b68423285912125d5fa22e5,
title = "Identifying Fake and Real Images by Using Masked Face Periocular Region",
abstract = "In this paper, we focus on the face spoofing of masked images to determine whether a masked person is real or fake. We developed a dataset of spoofed masked images generated using the DALL.E 2 tool, performed the ROI extraction using the CNN-DLib detector, and extracted the features using BoVw-sift. We applied deep learning and machine learning algorithms. XGBoost and Xception achieved the highest accuracy of 92\% and 94\% to determine whether the images were real or fake. The approach was tested on the real-world masked face recognition dataset (RMFRD). This shows that periocular information can predict whether the masked image is real or fake.",
keywords = "DLib detector, Presentation attack, Spoofing, VGG16, Xception, periocular region",
author = "Udayasri Nannuri and Kaushik Roy and Jinsheng Xu and Tony Gwyn and Govan, \{Bianca T.\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023 ; Conference date: 24-07-2023 Through 27-07-2023",
year = "2023",
doi = "10.1109/CSCE60160.2023.00121",
language = "English",
series = "Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "714--718",
booktitle = "Proceedings - 2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023",
}