ABSTRACT:

There are several different techniques for biometric authentication. Iris recognition happens to be one of the most sophisticated and effective among them. It is mainly based on the pattern recognition method where in it identifies sharp and distinct patterns of the Iris that can accurately recognize the intended user. This recognition system is quite accurate and also gives improved performances. With the rise in the security breaches and other forms of authentication frauds, it is very important to have a stringent biometric system in place. In the proposed work, iris localization has been performed by using the Daugman’s algorithm which is an integro-differential operator capable of separating or segmenting out regular shapes. The Daugman’s algorithm also has a noise smoothening capability. Both these attributes make the Daugman’s algorithm a preferred choice for iris localization. Subsequent to the iris localization, feature extraction is carried out to compute the relatively non-varying and unique parameters of an iris image. The features computed in the work are Contrast, Correlation, Energy, Homogeneity, Mean, Standard Deviation, Entropy, RMS, Variance, Smoothness, Kurtosis and Skewness. The features tend to behave uniquely for different iris images. However, overlapping values are possible. The features are then fed to a neural network using the Levenberg-Marquardt back propagation training rule. After training the neural network with feature values of authorized images, the subsequent step is testing the neural network for accuracy. The standard MMU database has been used for design of the system. It has been found that the proposed system attains an accuracy of 99.7% which is higher compared to the previously existing system using the same database.

EXISTING SYSTEM:

The user Authentication is one of the key concern areas that form the part of secured access to data. Iris authentication and recognition approach that helps in authenticating the intended user utilizing the characteristic features of the iris. It has several other applications such as it is used in ATM’s, and biometric recognition systems. This system typically contains different phases of functioning. The figure below shows the process involved for the iris recognition system. It happens to be a very useful approach in most cases. Figure 1 shows the process of Iris Recognition system and its different steps. Iris recognition is a form of bio metric authentication system that uses high end mathematical techniques and processes on the digital image of the Iris of the eye. It is mainly based on the pattern recognition method where in it identifies sharp and distinct patterns of the Iris that can accurately recognize the intended user. This recognition system is quite accurate and also gives improved performances. With the rise in the security breaches and other forms of authentication frauds, it is very important to have a stringent biometric system in place. Especially in places of high importance like the banks and ATMs, it is useful. Different algorithms are employed to encode the different set of patterns that exist in the iris localization scheme. It is useful to know the user is the real person or someone else impersonating the intended person. The system maintains a database. The database is usually big and consists of large number of templates of the iris features. This is then matched by the search engine of the model for the recognition purpose.

PROPOSED SYSTEM:\

Blood The proposed system is based in improvement in iris recognition based on the Dugman’s algorithm for iris localization and the use of neural networks for classification. The proposed method detects pupil using Daugman’s integro differential operator (IDO) and subsequently trains a neural network classifier for the final classification.

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10