Laser & Optoelectronics Progress, Volume. 58, Issue 18, 1811024(2021)

Extracting Fingerprints from Surface of Curved Objects Using Computational Light-Field Imaging

Xingjun Liu1,2,3 and Yanting Lu1,2、*
Author Affiliations
  • 1Nanjing Institute of Astronomical Optics & Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing, Jiangsu 210042, China;
  • 2CAS Key Laboratory of Astronomical Optics & Technology, Nanjing Institute of Astronomical Optics & Technology, Nanjing, Jiangsu 210042, China;
  • 3School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China
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    Fingerprints are widely used in the fields of criminal investigation and identification due to their uniqueness and lifelong invariance. Recently, criminal investigation forensic cameras are commonly used to extract fingerprints by taking photos as the traditional fingerprint extraction methods destroy the original fingerprint. Aiming at the problem that a clear image of the surface fingerprint from a curved object cannot be obtained in one shot, this study introduces the computational light-field imaging for the surface fingerprint extraction from the curved object. First, the fingerprint light-field camera is designed according to the fingerprint-shooting scene and the digital refocusing algorithm is used to obtain the fingerprint image stack. Then, the image fusion algorithm based on the image sharpness evaluation obtains a clear fingerprint image from the curved surface. Experimental results show that the fingerprint light-field camera and processing algorithm designed using the method can effectively extract fingerprints from the surface of curved objects.

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    Xingjun Liu, Yanting Lu. Extracting Fingerprints from Surface of Curved Objects Using Computational Light-Field Imaging[J]. Laser & Optoelectronics Progress, 2021, 58(18): 1811024

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    Paper Information

    Category: Imaging Systems

    Received: Mar. 15, 2021

    Accepted: Apr. 27, 2021

    Published Online: Aug. 23, 2021

    The Author Email: Lu Yanting (ytlu@niaot.ac.cn)

    DOI:10.3788/LOP202158.1811024

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