• DocumentCode
    2682452
  • Title

    Fingerprint registration using genetic algorithms

  • Author

    Ammar, Hany H. ; Tao, Yongyi

  • Author_Institution
    Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    148
  • Lastpage
    154
  • Abstract
    In automated fingerprint identification systems, an efficient and accurate alignment algorithm in the preprocessing stage plays a crucial role in the performance of the whole system. We explore the use of genetic algorithms for optimizing the alignment of a pair of fingerprint images. To test its performance, we compare the implemented genetic algorithm with two other algorithms, namely, 2D and 3D algorithms. Based upon our experiment on 250 pairs of fingerprint images, we find that: genetic algorithms run ten times faster than a 3D algorithm with similar alignment accuracy; and genetic algorithms are 13% more accurate than a 2D algorithm, with the same running time. The conclusion drawn from this study is that a genetic algorithm approach is an efficient and effective approach for fingerprint image registration
  • Keywords
    fingerprint identification; genetic algorithms; image matching; image registration; performance evaluation; 2D algorithms; 3D algorithms; automated fingerprint identification systems; experiment; fingerprint image registration; genetic algorithms; image alignment; optimization; performance evaluation; Decision making; Fingerprint recognition; Genetic algorithms; Graphics; Image matching; Neural networks; Tellurium; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Application-Specific Systems and Software Engineering Technology, 2000. Proceedings. 3rd IEEE Symposium on
  • Conference_Location
    Richardson, TX
  • Print_ISBN
    0-7695-0559-7
  • Type

    conf

  • DOI
    10.1109/ASSET.2000.888069
  • Filename
    888069