Iris recognition using SVM and BP algorithms

Authors

  • Eman Abdulmunem Research Scholar, Department of Engineering Technology College of Education in Computer Science AL-Mustansiriya University Baghdad, Iraq
  • Safana H. Abbas Assistant Professor Department of Engineering Technology College of Education in Computer Science AL-Mustansiriya University Baghdad, Iraq

DOI:

https://doi.org/10.31695/IJERAT.2018.3262

Keywords:

Neural Network, Principal Component Analysis , Support Vector Machine , Back-propagation.

Abstract

Iris recognition means to recognize an iris image by using computational algorithms. Identifying people in Iris recognition technology show the highest accuracy. In this paper, the Principal Component Analysis (PCA) is used as a reduction algorithm which gives the reduced iris feature set that is recognized using Support Vector Machine (SVM) and Back-propagation(BP) algorithms. The accuracy of using PCA with SVM is increased from (62%- 90%), while using PCA with BP is decreased from (40%-3.4 %)for the variable number of persons (10-70).

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Published

2018-05-05

Issue

Vol. 4 No. 5 (2018): Vol 4 Issue 5 May 2018

Section

Articles

How to Cite

Iris recognition using SVM and BP algorithms. (2018). International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135) , 4(5), 30-39. https://doi.org/10.31695/IJERAT.2018.3262