Open AccessPersonal identification based on skin texture features from the forearm and multi‐modal imaging
Author(s) -
Bianconi F.,
Chirikhina E.,
Smeraldi F.,
Bontozoglou C.,
Xiao P.
Publication year - 2017
Publication title -
skin research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.521
H-Index - 69
eISSN - 1600-0846
pISSN - 0909-752X
DOI - 10.1111/srt.12348
Subject(s) - forearm , texture (cosmology) , artificial intelligence , identification (biology) , computer vision , computer science , pattern recognition (psychology) , biomedical engineering , medicine , anatomy , image (mathematics) , biology , botany
Background/purpose We investigate the use of skin texture features from the inner forearm as a means for personal identification. The forearm offers a number of potential advantages in that it is a fairly accessible area, and, compared with other zones such as fingertips, is less exposed to the elements and more shielded from wear. Methods We extract and combine skin textural features from two imaging devices (optical and capacitive) with the aim of discriminating between different individuals. Skin texture images from 43 subjects were acquired from three different body parts (back of the hand, forearm and palm); testing used the two sensors either separately or in combination. Results Skin texture features from the forearm proved effective for discriminating between different individuals with overall recognition accuracy approaching 96%. Conclusions We found that skin texture features from the forearm are highly individual‐specific and therefore suitable for personal identification. Interestingly, forearm skin texture features yielded significantly better accuracy compared to the skin of the back of the hand and of the palm of the same subjects.