Abstract
Human iris has a very unique pattern which is different for each person so it is possible to use it as a basic of biometric recognition. To identify texture in an image, texture analysis method can be used. There is some texture analysis method, one of them is wavelet that extract the feature of image based on energy. In this research made a simulation to identified eyes iris based on Daubechies wavelet transform. First, the image of iris is segmented from eye image then enhanced with histogram equalization. Then used Daubechies wavelet method to get the energy value. The next step is recognition using K-Nearest Neighbor as the data classification. Three experiments are done in the research, those are influence of number of samples in database, influence of Daubechies wavelet transform level, and influence of the number of testing samples to calculate the level of False Positive Rate. As the result, the highest accuracy is achieved using Daubechies 8 level 3 with three samples iris image saved is 93,50%. Then, the lowest accuracy is achieved using Daubechies 4 level 1 and 3, and Daubechies 6 level 1 with one sample iris image saved is 91,50%.
 Keywords: biometric, human iris, texture analysis, Daubechies wavelet transform, K-Nearest Neighbor