Palmprint Identification Based on DWT, DCT and QPCA
K. P. Shashikala1, K. B. Raja2
1K P Shashikala, Ph.D. Registration Number: PP ECE. 0022, Subject of registration: Development of Efficient Algorithms for Biometric Security System using Palmprint, Rayalseema University, Kurnool, (A.P), India.
2K B Raja, Electronics and Communication Department, Bangalore University/ University Visveswaraya College of Engineering (UVCE), Bangalore, India.
Manuscript received on May 17, 2012. | Revised Manuscript received on June 22, 2012. | Manuscript published on June 30, 2012. | PP: 325-331 | Volume-1 Issue-5, June 2012. | Retrieval Number: E0531061512/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An individual can be identified effectively using palmprints. In this paper we propose palmprint identification based on DWT, DCT and QPCA (PIDDQ). Histogram equalization is used on palmprint to enhance contrast of an image. The DWT is applied on Histogram equalized image to generate LL, LH, HL and HH bands. The LL band is converted into DCT coefficients using DCT. QPCA is applied on DCT coefficients to generate features. The test and database palmprint features are compared using Euclidean Distance (ED). It is observed that the proposed method gives better performance compared to existing method.
Keywords: Palmprint Identification, DWT, DCT, QPCA, ED.