Wavelet Types Comparison for Extracting Iris Feature Based on Energy Compaction

3rd International Conference on Science & Engineering in Mathematics, Chemistry and Physics 2015

数学;化学;物理学

Isnanto, R. Rizal^1

Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Jalan Prof. Soedarto S.H., Tembalang, Semarang

50278, Indonesia^1

关键词: Biometric recognition;    Comparison analysis;    Energy compaction;    Histogram equalizations;    Iris features;    Recognition rates;    Texture analysis method;    Wavelet coefficients;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/622/1/012042/pdf
DOI  :  10.1088/1742-6596/622/1/012042

来源: IOP

【 摘 要 】

Human iris has a very unique pattern which is possible to be used as a biometric recognition. To identify texture in an image, texture analysis method can be used. One of method is wavelet that extract the image feature based on energy. Wavelet transforms used are Haar, Daubechies, Coiflets, Symlets, and Biorthogonal. In the research, iris recognition based on five mentioned wavelets was done and then comparison analysis was conducted for which some conclusions taken. Some steps have to be done in the research. First, the iris image is segmented from eye image then enhanced with histogram equalization. The features obtained is energy value. The next step is recognition using normalized Euclidean distance. Comparison analysis is done based on recognition rate percentage with two samples stored in database for reference images. After finding the recognition rate, some tests are conducted using Energy Compaction for all five types of wavelets above. As the result, the highest recognition rate is achieved using Haar, whereas for coefficients cutting for C(i)