@inproceedings{bd18a5fcfeb4423aa18b0982d2afc5c0,
title = "Palmprint recognition using siamese network",
abstract = "Recently, palmprint representation using different descriptors under the incorporation of deep neural networks, always achieves significant recognition performance. In this paper, we proposed a novel method to achieve end-to-end palmprint recognition by using Siamese network. In our network, two parameter-sharing VGG-16 networks were employed to extract two input palmprint images{\textquoteright} convolutional features, and the top network directly obtained the similarity of two input palmprints according to their convolutional features. This method had a good performance on PolyU dataset and achieved a high recognition outcome with an Equal Error Rate (EER) of 0.2819\%. To test the robustness of the proposed algorithm, we collected a palmprint dataset called XJTU from the practical daily environment. On XJTU, the EER of our method is 4.559\%, which highlighted a promising potential of the usage of palmprint in personal identification system.",
keywords = "Convolutional neural networks, Feature extraction, Palmprint recognition, Siamese network",
author = "Dexing Zhong and Yuan Yang and Xuefeng Du",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 13th Chinese Conference on Biometric Recognition, CCBR 2018 ; Conference date: 11-08-2018 Through 12-08-2018",
year = "2018",
doi = "10.1007/978-3-319-97909-0\_6",
language = "英语",
isbn = "9783319979083",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "48--55",
editor = "Zhenan Sun and Shiguang Shan and Zhenhong Jia and Kurban Ubul and Jie Zhou and Jianjiang Feng and Zhenhua Guo and Yunhong Wang",
booktitle = "Biometric Recognition - 13th Chinese Conference, CCBR 2018, Proceedings",
}