Your browser doesn't support javascript.
loading
Personal identification based on skin texture features from the forearm and multi-modal imaging.
Bianconi, F; Chirikhina, E; Smeraldi, F; Bontozoglou, C; Xiao, P.
Afiliação
  • Bianconi F; Department of Engineering, Università degli Studi di Perugia, 06125 Perugia, Italy.
  • Chirikhina E; School of Electrical Engineering and Computer Science, Queen Mary, University of London, London E1 4NS, UK.
  • Smeraldi F; School of Engineering, London South Bank University, London, SE1 0AA, UK.
  • Bontozoglou C; Sinlen Beauty Clinic, Sidcup DA14 6NF, UK.
  • Xiao P; School of Electrical Engineering and Computer Science, Queen Mary, University of London, London E1 4NS, UK.
Skin Res Technol ; 23(3): 392-398, 2017 Aug.
Article em En | MEDLINE | ID: mdl-27868246
ABSTRACT
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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pele / Reconhecimento Automatizado de Padrão / Registros / Imagem Multimodal Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Skin Res Technol Assunto da revista: DERMATOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pele / Reconhecimento Automatizado de Padrão / Registros / Imagem Multimodal Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Skin Res Technol Assunto da revista: DERMATOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Itália