High Biometric Recognition Based on Histogram and Semi-discrete Matrix Decomposition via Neural Network

Abstract

Iris recognition is regarded as the most reliable and accurate biometric identification system available highly protected and stable.Iris situating is the main focus in the procedure of iris recognition and verifies the precision of identification. In this work, a new algorithmfor iris localization is suggested based on the median filter and the histogram to determine an automated global threshold and the pupil centre. An algebraic based on semi-discrete matrix decomposition SDD is used to extract iris feature from iris image that decrease the difficultyininput layered neural network,thesizes of input patterns are enhanced. The iris recognition is developed by a neural network with differential adaptive learning rate to identify the iris features. This method is simple,effective and high speed recognition. The system is implemented by using Matlab. Experimental outcomes indicate that the suggested algorithm gives the accuracy of 100 % with time equal 1.4 sec is best than other methods for Daugman and Wildes.

Keywords

• iris recognition
• biometric identification
• pattern recognition
• medianfilter
• histogram
• semi discrete decomposition
• gradient descent algorithm
• singular value decomposition
• self
• organizing map