Context based face spoofing detection using active near-infrared images

In this paper, with the help of controllable active near-infrared (NIR) lights, we construct near-infrared differential (NIRD) images. Based on reflection model, NIRD image is believed to contain the lighting difference between images with and without active NIR lights. Two main characteristics base...

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Bibliographic Details
Published in2016 23rd International Conference on Pattern Recognition (ICPR) pp. 4262 - 4267
Main Authors Xudong Sun, Lei Huang, Changping Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Cameras
Context
Face
Feature extraction
Histograms
Lighting
Media
Online AccessGet full text
DOI10.1109/ICPR.2016.7900303

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Summary:In this paper, with the help of controllable active near-infrared (NIR) lights, we construct near-infrared differential (NIRD) images. Based on reflection model, NIRD image is believed to contain the lighting difference between images with and without active NIR lights. Two main characteristics based on NIRD images are exploited to conduct spoofing detection. Firstly, there exist obviously spoofing media around the faces in most conditions, which reflect incident lights in almost the same way as the face areas do. We analyze the pixel consistency between face and non-face areas and employ context clues to distinguish the spoofing images. Then, lighting feature, extracted only from face areas, is utilized to detect spoofing attacks of deliberately cropped medium. Merging the two features, we present a face spoofing detection system. In several experiments on self collected datasets with different spoofing media, we demonstrate the excellent results and robustness of proposed method.
DOI:10.1109/ICPR.2016.7900303