Efficient Iris Recognition Using Multi-feature Fusion | ||
| Mansoura Journal for Computer and Information Sciences | ||
| Volume 13, Issue 1, December 2017, Pages 1-8 PDF (871.4 K) | ||
| Document Type: Original Research Articles. | ||
| DOI: 10.21608/mjcis.2017.311791 | ||
| Authors | ||
| Shaimaa A.M. Hegazy1; Mostafa G.M. Mostafa2; Ahmed Abu Elfetouh1 | ||
| 1Faculty of computers and information systems, I.S dep. Mansoura University, Egypt | ||
| 2Faculty of computers and information systems Ain Shams University , Egypt | ||
| Abstract | ||
| Biometric technologies are very important these days for improving the accuracy of protecting private data from unauthorized access. It helps overcome deficiencies of current security traditional systems. For the last decade, researchers are developing new methodologies that employ biometrics to boost security field. This article proposes effective methods for Iris recognition based on multi-feature fusion. A feature fusion approach is implemented to improve the iris recognition rate. In particular, Haar Wavelet Transformation (HWT) features and principal Component Analysis (PCA) are used to model the iris texture. Both approaches are fused to improve performance. Fusion results are compared to those from each feature alone and with other reported work. The results obtained with the proposed method are better than the currently reported results. | ||
| Keywords | ||
| Biometric system; SDUMLA Database; Iris Recognition; Daugman‟s Rubber sheet; Haar Wavelet Transformation (HWT); Principal Component Analysis (PCA); Euclidean Distance (ED) | ||
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