A Dimensionality Reduced Iris Recognition System with Aid of AI Techniques
Keywords:
feed forward back propagation neural network (FFBNN), adaptive median filter, unbalanced haar wavelet, modified multi text on histogram (MMTH), iris r
Abstract
Technologies that exploit biometrics have the potential for the identification and verification of individuals designed for controlling access to secured areas or materials. One of the biometrics used for the identification is iris. Many techniques have been developed for iris recognition so far. Here we propose a new iris recognition system utilizing unbalanced wavelet packets and FFBNN-ABC. In our proposed system, the eye images obtained from the iris database are preprocessed using the adaptive median filter to remove the noise. After removing the noise, iris part is localized by using contrast adjustment and active contour technique. Then unbalanced wavelet packets coefficients and Modified Multi Text on Histogram (MMTH) features are extracted from the localized iris image. Then MMTH features extracted are clustered by using the MFCM technique. After clustering, the dimensionality of the features is reduced by using PCA. Then the dimensionality reduced features
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Published
2014-03-15
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Copyright (c) 2014 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.