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Proceedings Paper

Fingerprint spoof detection using wavelet based local binary pattern
Author(s): Supawan Kumpituck; Dongju Li; Hiroaki Kunieda; Tsuyoshi Isshiki
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Paper Abstract

In this work, a fingerprint spoof detection method using an extended feature, namely Wavelet-based Local Binary Pattern (Wavelet-LBP) is introduced. Conventional wavelet-based methods calculate wavelet energy of sub-band images as the feature for discrimination while we propose to use Local Binary Pattern (LBP) operation to capture the local appearance of the sub-band images instead. The fingerprint image is firstly decomposed by two-dimensional discrete wavelet transform (2D-DWT), and then LBP is applied on the derived wavelet sub-band images. Furthermore, the extracted features are used to train Support Vector Machine (SVM) classifier to create the model for classifying the fingerprint images into genuine and spoof. Experiments that has been done on Fingerprint Liveness Detection Competition (LivDet) datasets show the improvement of the fingerprint spoof detection by using the proposed feature.

Paper Details

Date Published: 8 February 2017
PDF: 8 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251C (8 February 2017); doi: 10.1117/12.2266852
Show Author Affiliations
Supawan Kumpituck, Tokyo Institute of Technology (Japan)
Dongju Li, Tokyo Institute of Technology (Japan)
Hiroaki Kunieda, Tokyo Institute of Technology (Japan)
Tsuyoshi Isshiki, Tokyo Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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