Description
Fingerprints have been widely used as a practical method of biometrics authentication or identification with a significant level of security. However, several spoofing methods have been used in the last few years to bypass fingerprint scanners, thus compromising data security.

Fingerprints have been widely used as a practical method of biometrics authentication or identification with a significant level of security. However, several spoofing methods have been used in the last few years to bypass fingerprint scanners, thus compromising data security. The most common attacks occur by the use of fake fingerprint during image capturing. Imposters can build a fake fingerprint from a latent fingerprint left on items such as glasses, doorknobs, glossy paper, etc. Current mobile fingerprint scanning technology is incapable of differentiating real from artificial fingers made from gelatin molds and other materials. In this work, the adequacy of terahertz imaging was studied as an alternative fingerprint scanning technique that will enhance biometrics security by identifying superficial skin traits. Terahertz waves (0.1 – 10 THz) are a non-ionizing radiation with significant penetration depth in several non-metallic materials. Several finger skin features, such as valley depth and sweat ducts, can possibly be imaged by employing the necessary imaging topology. As such, two imaging approaches 1) using quasi-optical components and 2) using near-field probing were investigated. The numerical study is accomplished using a commercial Finite Element Method tool (ANSYS, HFSS) and several laboratory experiments are conducted to evaluate the imaging performance of the topologies. The study has shown that terahertz waves can provide high spatial resolution images of the skin undulations (valleys and ridges) and under certain conditions identify the sweat duct pattern.
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    Title
    • Skin tissue terahertz imaging for fingerprint biometrics
    Contributors
    Date Created
    2017
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.S., Arizona State University, 2017
      Note type
      thesis
    • Includes bibliographical references (pages 58-61)
      Note type
      bibliography
    • Field of study: Electrical engineering

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    by Peng Zheng

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