Iris Recognition Based on Combined Feature of GLCM and Wavelet Transform

Author

Tallapragada, V.V.S. ; Rajan, E.G.

Author_Institution

Dept. of E.C.E., C.B.I.T., Hyderabad, India

fYear

2010

fDate

5-7 Aug. 2010

Firstpage

205

Lastpage

210

Abstract

Iris biometric is considered to be one of the most efficient and trusted biometric method for authenticating users. This paper presents a method for iris recognition based on hybrid feature set of wavelet and GLCM features, a non-filter based technique, combined with Haar wavelet transform to increase the efficiency of the system. Here we combine frequency domain feature with spatial domain feature to increase overall efficiency of system. Probability neural Network is used to classify the features. Results show that the overall system efficiency is 94% with false rejection rate higher than false acceptance rate. The technique is tested on CASIA Iris database.

Keywords

Haar transforms; authorisation; iris recognition; wavelet transforms; CASIA iris database; GLCM; Haar wavelet transform; frequency domain feature; iris biometric; iris recognition; nonfilter based technique; probability neural network; spatial domain feature; user authentication; Classification algorithms; Correlation; Feature extraction; Iris recognition; Pixel; Wavelet transforms; GLCM; Iris; Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Integrated Intelligent Computing (ICIIC), 2010 First International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4244-7963-4

Electronic_ISBN

978-0-7695-4152-5

Type

conf

DOI

10.1109/ICIIC.2010.48

Filename

5571456