Perbandingan Ekstraksi Ciri Haar Wavelet dan Log-Gabor Wavelet pada Pengenalan Iris Mata dengan VFI5

Abstract

A biometric system provides automatic identification based on unique feature or characteristic by the individual. As an example, the iris pattern of human eye is used in biometric system. Iris pattern is more stable and unique so it is suitable for biometric system. This research aims to compare dimension of Haar wavelet and Log-Gabor wavelet as feature extraction on iris recognition using VFI5 algorithm and provides implementation for recognizing eye images based on VFI5 algorithm. The eye images in this research are taken from CASIA dataset. The system uses Canny edge detector for image segmentation and Daugman’s Rubber Sheet Model to normalize the result to constant interval. Feature extraction uses Haar wavelet with 3 different levels and iris recognition with VFI5 algorithm with 3-cross fold validation. As a result, the best recognition of testing data is obtained from combining the votes from the left and right eyes. Less dimensions and features are obtained when using Haar wavelet than Log-Gabor wavelet.