@inproceedings{4c03dd049a8a4042b00e30662361b451,
title = "Palmprint liveness detection by combining binarized statistical image features and image quality assessment",
abstract = "This paper proposes a method based on Binarized Statistical Image Features (BSIF) and Image Quality Assessment for palmprint anti-spoofing approach. Firstly, BSIF computes a binary code for each pixel by filters, whose basis vectors are learnt from natural images via independent component analysis. For palmprint, it provides more texture information than the features in the original image. Image Quality Assessments are suitable measures since the recaptured images have features of blur and less details. Secondly, a new feature vector is formed by the former feature vectors. Finally, a SVM classifier is trained to discriminate the live and fake palmprint image. We collect a new database using iphone5 and iphone5s, which is the first one for palmprint liveness detection. Experiments on this database show great efficiency and high accuracy.",
keywords = "BSIF, Biometrics technology, Image quality assessment, Live palmprint detection",
author = "Xiaoming Li and Wei Bu and Xiangqian Wu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 10th Chinese Conference on Biometric Recognition, CCBR 2015 ; Conference date: 13-11-2015 Through 15-11-2015",
year = "2015",
doi = "10.1007/978-3-319-25417-3\_33",
language = "英语",
isbn = "9783319254166",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "275--283",
editor = "Jucheng Yang and Zhenan Sun and Shiguang Shan and Jinfeng Yang and Jianjiang Feng and Weishi Zheng",
booktitle = "Biometric Recognition - 10th Chinese Conference, CCBR 2015, Proceedings",
address = "德国",
}