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Face Liveness Detection Using Thermal Face-CNN with External Knowledge.
- Source :
- Symmetry (20738994); Mar2019, Vol. 11 Issue 3, p360, 1p
- Publication Year :
- 2019
-
Abstract
- Face liveness detection is important for ensuring security. However, because faces are shown in photographs or on a display, it is difficult to detect the real face using the features of the face shape. In this paper, we propose a thermal face-convolutional neural network (Thermal Face-CNN) that knows the external knowledge regarding the fact that the real face temperature of the real person is 36~37 degrees on average. First, we compared the red, green, and blue (RGB) image with the thermal image to identify the data suitable for face liveness detection using a multi-layer neural network (MLP), convolutional neural network (CNN), and C-support vector machine (C-SVM). Next, we compared the performance of the algorithms and the newly proposed Thermal Face-CNN in a thermal image dataset. The experiment results show that the thermal image is more suitable than the RGB image for face liveness detection. Further, we also found that Thermal Face-CNN performs better than CNN, MLP, and C-SVM when the precision is slightly more crucial than recall through F-measure. [ABSTRACT FROM AUTHOR]
- Subjects :
- THERMOGRAPHY
ARTIFICIAL neural networks
Subjects
Details
- Language :
- English
- ISSN :
- 20738994
- Volume :
- 11
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Symmetry (20738994)
- Publication Type :
- Academic Journal
- Accession number :
- 135627443
- Full Text :
- https://doi.org/10.3390/sym11030360