Fingerprint image enhancement using data driven DirectionalFilter Bank

Mohammad A U Khan, Tariq M. Khan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


A new method based upon data driven tool, principal component analysis (PCA), for fingerprint enhance-ment is proposed in this paper. PCA is a very useful statistical technique that has found application inmany different fields like image compression, face recognition and is commonly used for finding patternsin data of high dimension. In the proposed method, the input image is first decomposed into directionalimages using decimation free Directional Filter Bank (DDFB). Then these directional images are normal-ized. A data driven technique PCA is applied to these normalized directional fingerprint images, whichgives the PCA filtered images. These are basically directional images. Then these directional images arereconstructed into one image which is the enhanced one. Simulation results are included illustrating thecapability of the proposed method.

Original languageEnglish
Pages (from-to)6063-6068
Number of pages6
Issue number23
Publication statusPublished - Dec 2013
Externally publishedYes


  • Bank (DFB)
  • Bank(DDFB)
  • Decimation free
  • Directional
  • Filter
  • Fingerprint image enhancement
  • Principal component analysis analysis

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