Fingerprints identification using contour let transform
Joint Authors
al-Azzawi, M. K. M.
Salman, T. M.
Source
Engineering and Technology Journal
Issue
Vol. 35, Issue 3A (31 Mar. 2017), pp.282-288, 7 p.
Publisher
Publication Date
2017-03-31
Country of Publication
Iraq
No. of Pages
7
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
This paper suggests the use of contourlet transform for efficient feature extraction of fingerprints for identification purposes.
Back propagated neural network is then used as a classifier.
Two fingerprints databases are used to test the system.
These include fingerprints images with different positions, rotations and scales to test the robustness of the system.
Computer simulation results show that the proposed contourlet transform outperforms the classical wavelet method.
Where an identification rate of 94.4% was obtained using contourlet transform compare with 87% using wavelet transform for standard FVC2002 database.
American Psychological Association (APA)
Salman, T. M.& al-Azzawi, M. K. M.. 2017. Fingerprints identification using contour let transform. Engineering and Technology Journal،Vol. 35, no. 3A, pp.282-288.
https://search.emarefa.net/detail/BIM-770536
Modern Language Association (MLA)
Salman, T. M.& al-Azzawi, M. K. M.. Fingerprints identification using contour let transform. Engineering and Technology Journal Vol. 35, no. 3A (2017), pp.282-288.
https://search.emarefa.net/detail/BIM-770536
American Medical Association (AMA)
Salman, T. M.& al-Azzawi, M. K. M.. Fingerprints identification using contour let transform. Engineering and Technology Journal. 2017. Vol. 35, no. 3A, pp.282-288.
https://search.emarefa.net/detail/BIM-770536
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 287
Record ID
BIM-770536