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Texture based Palmprint Recognition using Simple Methods

by Aravind Nalamothu, Hemantha Kumar Kalluri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 4
Year of Publication: 2012
Authors: Aravind Nalamothu, Hemantha Kumar Kalluri
10.5120/7761-0827

Aravind Nalamothu, Hemantha Kumar Kalluri . Texture based Palmprint Recognition using Simple Methods. International Journal of Computer Applications. 50, 4 ( July 2012), 26-29. DOI=10.5120/7761-0827

@article{ 10.5120/7761-0827,
author = { Aravind Nalamothu, Hemantha Kumar Kalluri },
title = { Texture based Palmprint Recognition using Simple Methods },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 4 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number4/7761-0827/ },
doi = { 10.5120/7761-0827 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:49:07.495167+05:30
%A Aravind Nalamothu
%A Hemantha Kumar Kalluri
%T Texture based Palmprint Recognition using Simple Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 4
%P 26-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now-a-Days Biometric based recognition is the most popular human recognition pattern. Biometric based recognition is an approach using the biological features inherent in each individual. They are processed based on the identical, portable and arduous duplicate characteristics. In the Palmprint recognition application implementing more details apart from principle lines or minutiae will be much helpful. In this paper, proposed a texture based palmprint recognition system. It is suitable to large organizations for maintaining employee entry record. Here, presents an algorithm to extract the features from region of interest (ROI) of palmprint images. In this approach 128 X 128 ROI images of the Hong Kong Polytechnic University 2D_3D_ palmprint database. From these images, extracted some texture features by using of simple methods. Training set is prepared with the help of K no. of samples per user, where K varies from 1to 4. Results are checked against remaining images in image recognition mode. Results are encouraging.

References
  1. J. Lu, Y. Zhao and J. Hu, "Enhanced Gabor-based region covariance matrices for palmprint recognition", International Journal of Electronics Letters, Aug 2009.
  2. Wang Xuan, Lei Li and Wang Mingzhe, "Palmprint Verification based on 2D – Gabor Wavelet and Pulse Coupled Neural Network", knowl. Based Syst(2011),doi:10. 1016/j. knosys.
  3. W. Li, D. Zhang and Z. Xu, "Palmprint Identification by Fourier Transfor", International Journal of Pattern Recognition and Artificial Intelligence, 417-432-2002.
  4. Manisha, Madhuri and Neena, "Texture Based Palmprint Identification Using DCT features", International conference on Advances in Pattern Recognition, 978-0-7695-3520-3/09.
  5. Pritee and deepti, "Analysis of palmprint Verification using Wavelet filter and competitive code", International conference on computational Intelligence and communication Systems. 978-0-7695-4254-6/10.
  6. H Imatiaz and S A Fattah, "A Spectral Domain Dominant Feature Extraction Algorithm for Palmprint Recognition", International Journal of Image processing (IJIP), Volume-5,2011
  7. "Digital Image Processing", 3rd Edition, by Rafael C, Gonzalez, Richard E woods.
  8. The Hong Kong Polytechnic University 2D_3D_Palmprint Database, http://www. comp. polyu. edu. hk/~biometrics/2D_3D_palmprint. htm
  9. Wikipedia http://en. wikipedia. org/wiki/
Index Terms

Computer Science
Information Sciences

Keywords

Biometric Palmprint Recognition Texture Based Recognition Pattern Recognition Canberra Distance

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