Subcutaneous sweat pore estimation from optical coherence tomography

Autor: Baojin Ding, Haixia Wang, Peng Chen, Yilong Zhang, Ronghua Liang, Yipeng Liu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IET Image Processing, Vol 15, Iss 13, Pp 3267-3280 (2021)
Druh dokumentu: article
ISSN: 1751-9667
1751-9659
DOI: 10.1049/ipr2.12322
Popis: Abstract Abstract Sweat pore, one of the level 3 features of fingerprint, has attracted much attention in fingerprint recognition. Traditional sweat pores on surface fingerprint are unclear or blurred when fingers are stained or damaged. Subcutaneous sweat pores, as cross section of the sweat glands, are resistant to external interferences. With 3D fingertip information measured by optical coherence tomography (OCT), the subcutaneous sweat pore estimation from OCT volume data is investigated. First, an adaptive subcutaneous pore image reconstruction method is proposed. It utilizes the skin surface and viable epidermis junction as reference and realizes depth‐adaptive pore image reconstruction. Second, a dilated U‐Net combining the U‐Net with dilated convolution is proposed for subcutaneous sweat pore extraction, which can prevent information loss of sweat pores caused by downsampling. To the best knowledge, it is the first time that subcutaneous sweat pore extraction is investigated and proposed. Experiments on subcutaneous pore image reconstruction and sweat pore extraction are both conducted. The qualitative and quantitative results show that the proposed adaptive method performs better in subcutaneous pore image reconstruction compared with the fix‐depth method, and the dilated U‐Net outperforms other methods on subcutaneous sweat pore extraction.
Databáze: Directory of Open Access Journals
Externí odkaz: