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Iris Recognition & Personal Authentication System Improve Efficiency

Authors :
Rajput, Anil; Dept. of Maths & Computer Science, Sadhuvasvani College, Bhopal (M.P.) India
Sant, Anjali; Dept. of Maths, BITS, Bhopal (M.P.) India
Singh, Manmohan; Department of Computer Science, BIST, Bhopal (M.P.) India
Shrivastava, Shivshakti; Department of Computer Application, SCOPE, Bhopal (M.P.) India
Rajput, Anil; Dept. of Maths & Computer Science, Sadhuvasvani College, Bhopal (M.P.) India
Sant, Anjali; Dept. of Maths, BITS, Bhopal (M.P.) India
Singh, Manmohan; Department of Computer Science, BIST, Bhopal (M.P.) India
Shrivastava, Shivshakti; Department of Computer Application, SCOPE, Bhopal (M.P.) India
Source :
Binary Journal of Data Mining & Networking; Vol 1, No 1 (2010): BINARY JOURNAL OF DATA MINING & NETWORKING; 2229–7170
Publication Year :
2010

Abstract

Our objective is to prepare the system that provides the security for an organization. The system is based on an empirical analysis of the iris image and it is split in several steps using local image properties. The system steps are capturing iris patterns; determine the location of the iris boundaries; converting the iris boundary to the stretched polar coordinate system; extracting the iris code based on texture analysis using wavelet transforms; and classification of the iris code. The proposed system use the wavelet transforms for texture analysis, and it depends heavily on knowledge of the general structure of a human iris. The system was implemented and tested using a dataset of 240 samples of iris data with different contrast quality. The classification rate compared with the well known methods discussed.Keywords: data mining, AI, information, Neural Network.

Details

Database :
OAIster
Journal :
Binary Journal of Data Mining & Networking; Vol 1, No 1 (2010): BINARY JOURNAL OF DATA MINING & NETWORKING; 2229–7170
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1136901103
Document Type :
Electronic Resource