Title :
A fourier transform quality measure for iris images
Author :
Makinana, Sisanda ; Van Der Merwe, Johannes J. ; Malumedzha, Tendani
Author_Institution :
Modelling & Digital Sci., Council for Sci. & Ind. Res., Pretoria, South Africa
Abstract :
Iris recognition systems have attracted much attention for their uniqueness, stability and reliability. However, performance of this system depends on quality of acquired iris sample. This is because in order to obtain reliable features good quality images are to be used. Thus, it is important to accurately assess image quality before applying feature extraction algorithm in order to avoid insufficient results. This study aims to quantitatively analyse the effect of iris image quality in order to ensure that good quality images are selected for feature extraction, in order to improve iris recognition system. In addition, this research proposes a measure of iris image quality using a Fourier Transform. The experimental results demonstrate that the proposed algorithm shows better performance in quality classification as it yields a 97% accuracy rate than the existing algorithms.
Keywords :
Fourier transforms; feature extraction; iris recognition; Fourier transform; feature extraction algorithm; iris image quality; iris recognition system; Feature extraction; Fourier transforms; Frequency measurement; Image quality; Iris; Iris recognition; Standards; Fourier Transform; image quality; quality measure;
Conference_Titel :
Biometrics and Security Technologies (ISBAST), 2014 International Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-6443-7
DOI :
10.1109/ISBAST.2014.7013093