A robust and efficient fingerprint image restoration method based on a phase-field model

Yibao Li, Qing Xia, Chaeyoung Lee, Sangkwon Kim, Junseok Kim

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


In this study, we present a robust and efficient fingerprint image restoration algorithm using the nonlocal Cahn–Hilliard (CH) equation, which was proposed for modeling the microphase separation of diblock copolymers. We take a small local region embedding the damaged domain and solve the nonlocal CH equation to restore the fingerprint image. A Gauss–Seidel type iterative method, which is efficient and simple to implement, is used. The proposed method has the advantage in that the pixel values in the damaged fingerprint domain can be obtained using the image information from the outside of the damaged fingerprint region. Fingerprint restoration based on adjacent pixel information can ensure the accuracy of the fingerprint information with a low computational cost. Computational experiments demonstrated the superior performance of the proposed fingerprint restoration algorithm.

Original languageEnglish
Article number108405
JournalPattern Recognition
Publication statusPublished - 2022 Mar


  • Diblock copolymer
  • Fingerprint restoration
  • Nonlocal Cahn–Hilliard equation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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