WBM- White Black Mass Estimation Technique Based Iris Recognition for Improved Biometric Authentication
S. Rama Lavanya, R. S. Sabeenian · Transylvanian Review · 2016
The biometric authentication based on iris segmentation has been well equipped with more strategic approaches, but suffers with the problem of false authentication and higher error rate. To overcome such deficiency in biometric authentication, an white black mass (WBM) estimation technique has been discussed in this paper. The method starts with the application of gabor filter which performs noise removal in different orientation and applies filter in multiple levels. Then the method extract the features like iris, limbic and pupil. From the extracted features, the method computes the white black mass estimation on each block considered. The method splits the pupil region into four quarters and for each quarter the white black mass is estimated. Similarly, the method computes the WBM for the limbic region. Using the computed WBM values, the method computes the biometric weight towards each class of iris image stored. The method produces more efficient result in biometric authentication and reduces the false authentication ratio.