@inproceedings{405d2eea4d514ef6a32961bcbb23f47f,
title = "Face recognition based on Extended Symmetric Local Graph Structure",
abstract = "Face recognition is an important area in biometrics and computer vision. A lot of feature extraction can handle face recognition method such as checking pixel neighbor. Local Binary Pattern, Local Graph Structure, and Symmetric Local Graph Structure are an operator of the feature extraction. This research called Extended Symmetric Local Graph Structure which it is an improvement operator from SLGS to build more symmetric neighbor. The result of ESLGS has average accuracy 84.24% in one until five retrieval similarity of YALE dataset image and 80.59% in one until five retrieval similarity of ORL dataset image. The conclusion indicates that our proposed operator has more accuracy than LBP, LGS and SLGS operator. Advantage of proposed method is to provide better performance in accuracy and complexity than other operator.",
keywords = "Face Recognition, Image Retrieval, Symmetric Local Graph Structure",
author = "Yunanto, {Andhik Ampuh} and Darlis Herumurti",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016 ; Conference date: 12-10-2016",
year = "2017",
month = apr,
day = "24",
doi = "10.1109/ICTS.2016.7910277",
language = "English",
series = "Proceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "80--84",
booktitle = "Proceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016",
address = "United States",
}