Biometrics Fingerprint Recognition using Discrete Cosine Transform (DCT)

Biometric systems based on the fingerprint recognition are considered one of the most important identification techniques. It is a successful way to determine the identity of the person that cannot be faked or stolen easily. This study aims to identify fingerprint images through several steps and extract the features based on DCT technique. The fingerprint image is divided into sub-blocks and allows evaluating the statistical features from the DCT Coefficients .The matching process is implemented using the correlation between fingerprint images. The obtained results include an efficient recognition using DCT.These programs are implemented via MATLAB environment.

[1]  D. Indradevi,et al.  Efficient Fingerprint Recognition Through Improvement of Feature Level Clustering, Indexing and Matching Using Discrete Cosine Transform , 2011 .

[2]  Venu Govindaraju.  Biometrics and Security , 2009, ICISS.

[3]  Carlo Sansone,et al.  Combining perspiration- and morphology-based static features for fingerprint liveness detection , 2012, Pattern Recognit. Lett..

[4]  Fayadh M. Abed,et al.  Fingerprint image Pre- post processing Methods for minutiae extraction , 2009 .

[5]  Abdullah Çavusoglu,et al.  A fast fingerprint image enhancement algorithm using a parabolic mask , 2008, Comput. Electr. Eng..

[6]  Hafiz Imtiaz,et al.  A Novel Pre-processing Technique for DCT- domain Palm-print Recognition , 2012 .

[7]  K. Hemachandran,et al.  A Secondary Fingerprint Enhancement and Minutiae Extraction , 2012 .

[8]  Arun Ross,et al.  An introduction to biometrics , 2008, ICPR 2008.

[9]  K B Raja,et al.  Performance Evaluation of Fingerprint Identification Based on DCT and DWT using Multiple Matching Techniques. , 2011 .

[10]  Wang Jian-kan.  Fingerprint Indexing Based on Singular Points’ Orientation Field , 2010 .

[11]  Feryal I. Haj Hassan,et al.  Fingerprint Image Enhancement , 2010 .

[13]  Isra H. Al-Ani,et al.  Journal of Emerging Trends in Computing and Information Sciences Gait Recognition Based Improved Histogram , 2022 .

[14]  Asker M. Bazen,et al.  Fingerprint Identification - Feature Extraction, Matching and Database Search , 2002 .

[15]  Kulwinder Singh,et al.  Fingerprint Feature Extraction , 2011 .

[16]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[17]  Bassam Muhsin Khalil Alobaidi.  Fingerprint image enhancement , 1998 .