Anguli: Synthetic Fingerprint Generator
Beta Version

Database Systems Lab

Indian Institute of Science


 [About] [Download]
[Requirements]
[User Guide]
[Contact]
[Team]
[Bibliography]


  About
     
      Welcome to the project  Anguli deployed at the Database Systems Lab, Indian Institute of Science. "Anguli" is a Hindi word and it means "Finger" in English. Anguli is a freely available C++ synthetic fingerprint generator. It is built with an intent to generate large scale fingerprint database. Since fingerprints are private and important data, none of the fingerprint databases are freely available. Anguli is of the great importance in academic studies of fingerprints, also it can help in testing fingerprint identification systems which are deployed at very large scale by governments. Anguli generates 1 million fingerprints in less than 4 days with 7 threads on 8 cores of 2 GHz.
        Anguli uses the algorithms from SFinGe publications given in
bibliography. This project is motivated from SFinGe.


  Download

     Windows:
           Anguli Win MSVC (32 bit) - 24.1 MB    
           Anguli Win MinGw (32 bit) - 26.7 MB

     Ubuntu:
           Anguli Linux (32 bit) - 15.2 MB
           Anguli Linux (64 bit) - 15.2 MB

     Anguli Source Code
          Anguli_src.tgz

     Demo Video
           Anguli.avi

     Sample Fingerprints Impressions:
          1K.tgz - 61.5 MB       10K.tgz - 615 MB
 

  Requirements
Windows-32 bit MSVC
.Net Framework 3.0 or above
Windows-32 bit MinGW
None
Linux- 32 bit
g++, OpenCv 4, Qt framework
Linux-64 bit
g++, OpenCv 4, Qt framework
  


  Contact



  Team




Bibliography
1.
A. H. Ansari, “Generation and storage of large synthetic fingerprint database,” M.E. Thesis, IISc, Jul. 2011.
2.
R. Cappelli and D. Maio and D. Maltoni, "Synthetic Fingerprint-Database Generation", Proceedings of 16th  International Conference on Pattern Recognition, vol 3, pages 744-747, 2002.
3.
R. Cappelli, "SFinGe: an Approach to Synthetic Fingerprint Generation", Proceedings of International Workshop on Biometric Technologies, pages 147-154, 2004.
4.
S. Jadhav, "Generating, Classifying and Indexing Large Scale Fingerprints", M.E. Thesis, IISc, Jun. 2012.
5.
D. Maltoni and D. Maio and A.K. Jain and S. Prabhakar, "Handbook of Fingerprint Recognition", Springer, 2003.
6.
B. Sherlock and D. Monroe, "A model for Interpreting Fingerprint Topology", Pattern Recognition, vol 26, pages 1047-1055, 1993.
7.
P. Vizcaya and L. Gerhardt, "A Nonlinear Orientation Model for Global Description of Fingerprints", Pattern Recognition, vol 29, pages 1221-1231, 1996.
8.
R. Cappelli and D. Maio and D. Maltoni, "An Improved Noise Model for the Generation of Synthetic Fingerprints", International Conference on Control, Automation, Robotics and Vision, Vol 2, pages 1250-1255, 2004.
9.
R. Cappelli and D. Maio and D. Maltoni, "Modeling Plastic Distortion in Fingerprint Images", Proceedings of 2nd International Conference on Advances in Pattern Recognition, vol 2013, pages 369-376, 2001.
10.
K. Wadhwani, “Large-scale fingerprint identification systems,” M.E. Thesis, IISc, Jul. 2011.