Open AccessRobust Iris Classification Based on Deep Neural Network (DNN) and Stationary Wavelet Transform (SWT)
Author(s) -
S. Priyanka,
Pavithra,
M. Pavithra,
S. Bhuvana
Publication year - 2019
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit19529
Subject(s) - iris recognition , artificial intelligence , computer science , iris (biosensor) , artificial neural network , feature extraction , pattern recognition (psychology) , wavelet transform , deep learning , wavelet , computer vision , biometrics
The eye is a vital part of our body. It consists of several layers like sclera, retina, tunica, and iris. Among these several layers, Iris plays a vital role in human visionary. There are various infections which affect the Iris functioning. The sign, symptoms, and diagnosis of this is still a challenge for doctors. To overcome this many techniques and technologies have been introduced. But still, the existing system has several drawbacks in recognition like a huge amount of dataset, classification, extraction, etc. To overcome this we propose a system where Deep Neural Network plays a major part. It classifies the iris disease in our eyes in a more clear and precise manner. In additional to Deep Neural Network several other algorithms have been used like Stationary Wavelet Transform, for image selection and recognition, Local Binary Pattern, for Feature extraction and at a final stage Deep Neural Network for classification of Iris images.