Paper Title : Human Iris Using Neural Network
ISSN : 2394-2231
Year of Publication : 2020
MLA Style: Dr.E.Punarselvam, Mr.S.Gopi ,M.Hariharan, T.Hariharan, M.Karthi. , J.Vimalaadhithyan, "Human Iris Using Neural Network" Volume 7 - Issue 2 March - April,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
APA Style: Dr.E.Punarselvam, Mr.S.Gopi ,M.Hariharan, T.Hariharan, M.Karthi. , J.Vimalaadhithyan, "Human Iris Using Neural Network" Volume 7 - Issue 2 March - April,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
Multi-biometric systems are being increasingly deployed in many large-scale biometric applications because they have several advantages such as lower error rates and larger population coverage compared to uni-biometric systems. However, multi-biometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. Traditional iris segmentation methods provide good results good result when iris images are recorded ideal imaging conditions. However the segmentation accuracy of an iris recognitions system considerably influences its performance especially in the case of non ideal iris images, iris datasets are collected from online for the further processes which are recorded in the visible and infrared imaging conditions are used, then fusion of an expanding and a shrinking active contour is developed for the iris segmentation by integration of a new pressure force on the active contour model. That is Active Contour Force (ACF) model is used for segmentation .To isolate the boundaries of an iris. Un circle normalization schema is employed to get normalized image from the segmented image.
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Language Integrated Query, Convolutional Neural Networks, Common Type System