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Multispectral Face Spoofing Detection Using VIS-NIR Imaging Correlation
Jul 11, 2018Author:
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Title: Multispectral Face Spoofing Detection Using VIS-NIR Imaging Correlation

Authors: Sun, XD; Huang, L; Liu, CP

Author Full Names: Sun, Xudong; Huang, Lei; Liu, Changping

Source: INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 16 (2):SI 10.1142/S0219691318400039 MAR 2018

Language: English

Abstract: With the wide applications of face recognition techniques, spoofing detection is playing an important role in the security systems and has drawn much attention. This research presents a multispectral face anti-spoofing method working with both visible (VIS) and near-infrared (NIR) spectra imaging, which exploits VIS-NIR image consistency for spoofing detection. First, we use part-based methods to extract illumination robust local descriptors, and then the consistency is calculated to perform spoofing detection. In order to further exploit multispectral correlation in local patches and to be free from manually chosen regions, we learn a confidence factor map for all the patches, which is used in final classifier. Experimental results of self-collected datasets, public Msspoof and PolyU-HSFD datasets show that the proposed approach gains promising results for both intra-dataset and cross-dataset testing scenarios, and that our method can deal with different illumination and both photo and screen spoofing.

ISSN: 0219-6913

eISSN: 1793-690X

Article Number: 1840003

IDS Number: GA6AW

Unique ID: WOS:000428416300004

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