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The IUP Journal of Information Technology
Iris Recognition Using Gabor Filter and SURF Feature Detection Technique†
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The paper presents an iris recognition system using Gabor filter and SURF feature detection technique. Several image preprocessing techniques have been performed followed by extraction of the iris image from the image of the eye. This process is followed by normalization and filtering for extraction. Convolution method has been deployed for the filtering process with the aid of Gabor filters. Finally, the SURF feature detection technique has been employed for comparing the results. The proposed method is simple and effective and has been implemented using MATLAB.

 
 

For efficient and reliable identification, biometrics uses different characteristics of the human race for the identification process. One such biometric technology is the iris recognition technology that utilizes iris for identifying the human beings based on the test results of the recognition methodology. The numerous distinctive features of the iris help in authentication of persons. Various methods have been employed in the past for extracting the iris features. In this methodology, the Gabor filter has been employed in two distinct methods. At first, the Gabor filter is employed on the entire image followed by the extraction of the unique features from that image. Thereafter, it is employed for the extraction of the information that is of local concern or features from the image that further sum up to give the global features. With the use of different number of filter banks containing 15, 20, 25, 30 and 35 filters, a comparison analysis is made between the obtained results. CASIA version 1 iris database has been used to perform and test the various results. The best accuracy of 99.16% is achieved after capturing the local information from the iris images and comparing the output feature vectors using the hamming distance.

 
 

Information Technology Journal, Recognition, Gabor filter, SURF detection