Iris Recognition Using Wavelet Transform and SVM BasedApproach

  • Sushilkumar S. Salve

Abstract

Inthis paper we proposed an improved novel approach
to identify the person using iris recognition technique. This
approach is based on fuzzy and support vector machine (SVM) as
an iris pattern classifier. Prior to classifier, region of interest i.e.
iris region is segmented using Canny edge detector and Hough
transform. Provided that the effect of eyelid and eyelashes get
reduced. Daugman’s rubber sheet model used to get normalized iris
to improve computational efficiency and proper dimensionality.
Further, discriminating feature sequence is obtained by feature
extraction from segmented iris image using 1D Log Gabor
wavelet.Encoding is done using phase quantization to get feature
vectors. These binary sequence feature vectors are used to train
SVM and fuzzy system as iris pattern classifier. The experimental
tests are performed over standard CASIAIrisV4 database.

Keywords: iris, segmentation, Gabor filters, SVM,FCM

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Salve, S. (2019). Iris Recognition Using Wavelet Transform and SVM BasedApproach. Asian Journal For Convergence In Technology (AJCT). Retrieved from http://www.asianssr.org/index.php/ajct/article/view/725
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