Thermal Face Verification through Identification
- Resource Type
- Authors
- Marcin Kowalski; Artur Grudzień; Norbert Palka
- Source
- Sensors
Volume 21
Issue 9
Sensors, Vol 21, Iss 3301, p 3301 (2021)
Sensors (Basel, Switzerland)
- Subject
- Computer science
TP1-1185
02 engineering and technology
Biochemistry
Convolutional neural network
Article
Analytical Chemistry
Image (mathematics)
Face verification
Thermal
convolutional neural networks
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Instrumentation
Artificial neural network
business.industry
Chemical technology
020206 networking & telecommunications
Percentage point
Pattern recognition
Atomic and Molecular Physics, and Optics
Identification (information)
face verification
Face (geometry)
020201 artificial intelligence & image processing
Artificial intelligence
business
long-wavelength infrared radiation
- Language
- English
- ISSN
- 1424-8220
This paper reports on a new approach to face verification in long-wavelength infrared radiation. Two face images were combined into one double image, which was then used as an input for a classification based on neural networks. For testing, we exploited two external and one homemade thermal face databases acquired in various variants. The method is reported to achieve a true acceptance rate of about 83%. We proved that the proposed method outperforms other studied baseline methods by about 20 percentage points. We also analyzed the issue of extending the performance of algorithms. We believe that the proposed double image method can also be applied to other spectral ranges and modalities different than the face.