Feature Fusion Based Iris and Retina Recognition System Using Kohonon Self-Organizing Mapping Neural Network Algorithm

Authors

  • Md. Rabiul Islam Department of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh Department of Electrical and Electronics Engineering, Daffodil International University, Dhaka, Bangladesh
  • Md. Fayzur rahman

DOI:

https://doi.org/10.37591/.v5i2.3078

Abstract

This paper proposes a model of biometric security with feature fusion based iris and retina recognition system. Though, a lot of research works have done for iris recognition system and it is not new for the fusion of multimodal iris recognition in the area of biometric security and authentication system. But, it is a relatively new idea of mixing iris and retina features for human authentication. Here, the features of iris and retinal images are extracted using standard methods, then features are fused and reduced using Principal Component Analysis based dimensionality reduction technique. These reduced features are feed to the Kohonon Self-Organizing Neural Network Algorithm for learning and recognition purposes. CASIA iris dataset have been used for iris recognition and DRIVE dataset have been used for performance measurements of the retinal images.

 

Keywords- Biometric Security, Feature Fusion Model, Self-Organizing Mapping Neural Network Algorithm, Dimensionality Reduction Technique

 

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Published

2019-08-14

Issue

Vol. 5 No. 2 (2015)

Section

Articles

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