Personal identification based on skin texture features from the forearm and multi-modal imaging
Journal article
Bianconi, F, Chirikhina, E, Smeraldi, F, Bontozoglou, C and Xiao, P (2016). Personal identification based on skin texture features from the forearm and multi-modal imaging. Skin Research and Technology. 23 (3), pp. 392-398. https://doi.org/10.1111/srt.12348
Authors | Bianconi, F, Chirikhina, E, Smeraldi, F, Bontozoglou, C and Xiao, P |
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Abstract | We investigate the use of skin texture features from the inner forearm as a means for personal identi- fication. 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. 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. Skin texture features from the forearm proved effective for discriminating between different individuals with overall recognition accuracy approaching 96%. 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. |
Keywords | image processing; personal identification; skin texture; texture analysis; 1103 Clinical Sciences |
Year | 2016 |
Journal | Skin Research and Technology |
Journal citation | 23 (3), pp. 392-398 |
Publisher | Blackwell Publishing |
ISSN | 0909-752X |
Digital Object Identifier (DOI) | https://doi.org/10.1111/srt.12348 |
Publication dates | |
19 Nov 2016 | |
Publication process dates | |
Deposited | 13 Jan 2017 |
Accepted | 18 Oct 2016 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/8716q
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