Skip to content

Latest commit

 

History

History
121 lines (68 loc) · 4.92 KB

README.md

File metadata and controls

121 lines (68 loc) · 4.92 KB
Raw

PCF: A Progressive and Corrective Feedback for Latent Fingerprint Enhancement

We understand the importance of transparency and reproducibility in research. To ensure a user-friendly experience, we are sharing the executable file. However, variations in environments can cause differences in results. Therefore, we also provide the results of NIST SD27, NIST SD302, IIITD MOLF, and IIITD MSLFD on https://skconan.github.io/SFP-Progressive-Feedback-Latent-Fingerprint-Restoration.

Requirements

  • Windows 10 or 11 operating system.

  • Storage 14 GB

    • ksip_lfp_enh_installer 300 MB
    • MATLAB_Runtime_R2022a_Update_6_win64 (installer 4 GB and install space required 8 GB)

Installation

Install MATLAB Runtime version R2022a (9.12)

  1. Download MATLAB Runtime from www.mathworks.com Or MATLAB_Runtime_R2022a_Update_6_win64.zip.

  2. Extract files and install MATLAB Runtime using setup.exe.

Install KSIP Latent Fingerprint Enhancement

  1. Download ksip_lfp_enh_installer.exe.

  2. Install KSIP LFP ENHANCEMENT using ksip_lfp_enh_installer.exe. The installation directory will be C:\Program Files (x86)\KSIP LFP ENHANCEMENT

  3. Setup environment path

    • Go to Environment Variables
    • Add C:\Program Files (x86)\KSIP LFP ENHANCEMENT in the Path variable under System variables.

    If KSIP LFP ENHANCEMENT installed in a different location, add that specific path to System variables instead of C:\Program Files (x86)\KSIP LFP ENHANCEMENT.


Usage

Preprocessing

Before performing fingerprint enhancement, the texture image needs to be extracted using Total Variation. Note use mu is 0.45. Ensure you have completed this step before proceeding with the enhancement process.

Enhancement

  1. Open Terminal or Windows Powershell

  2. Run ksip_pcf.exe <org_dir> <tv_dir> <seg_dir> <out_dir> and Enter.

     usage: ksip_pcf.exe <org_dir> <tv_dir> <seg_dir> <out_dir>

 arguments:
 
 <org_dir>     Original Fingerprint Image Directory
 <tv_dir>      Fingerprint Total Variation Directory
 <seg_dir>     Segment Directory
 <out_dir>     Output Directory

Example

  • Run NIST SD27 Enhancement

      ksip_pcf.exe D:\NIST_SD27\Latent D:\NIST_SD27\LatentTV D:\NIST_SD27\GlobalDict  D:\NIST_SD27\Enhancement

Output Example

Original Fingerprint Image DIrectory: D:\NIST_SD27\Latent
Fingerprint TV Image DIrectory: D:\NIST_SD27\LatentTV
Fingerprint Segment DIrectory: D:\NIST_SD27\GlobalDict
Fingerprint Enhanced DIrectory: D:\NIST_SD27\Enhancement
0001/0002 Start enhancement: 001L2U.bmp
0001/0002 Enhancement Success
0001/0002 Save enhanced image to D:\NIST_SD27\Enhancement\001L2U.bmp
0001/0002 Execution time: 25.36 second

Acknowledgements

This work was supported in part by the Department of Electrical Engineering, Faculty of Engineering, Kasetsart University, and in part by the Siew-Sngiem Karnchanachari Research Leadership and Young Professorship Awards.


License

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.


Citing PCF

If you are using PCF or benchmarks in your research, kindly reference the following.

@ARTICLE{9469797,
    author={Horapong, Kittipol and Srisutheenon, Kittinuth and Areekul, Vutipong},
    journal={IEEE Access}, 
    title={Progressive and Corrective Feedback for Latent Fingerprint Enhancement Using Boosted Spectral Filtering and Spectral Autoencoder}, 
    year={2021},
    volume={9},
    number={},
    pages={96288-96308},
    doi={10.1109/ACCESS.2021.3093879}
}

Or

K. Horapong, K. Srisutheenon and V. Areekul, "Progressive and Corrective Feedback for Latent Fingerprint Enhancement Using Boosted Spectral Filtering and Spectral Autoencoder," in IEEE Access, vol. 9, pp. 96288-96308, 2021, doi: 10.1109/ACCESS.2021.3093879.

Contact

If you have any questions or need assistance, reach us at [email protected] / [email protected] / [email protected].