作者
Kennedy Okokpujie, Etinosa Noma-Osaghae, Samuel John, Akachukwu Ajulibe
发表日期
2018
研讨会论文
IT Convergence and Security 2017: Volume 2
页码范围
203-211
出版商
Springer Singapore
简介
It is quite easy to spoof an automated iris recognition system using fake iris such as paper print and artificial lens. False Rejection Rate (FRR) and False Acceptance Rate (FAR) of a specific approach can be as a result of noise introduced in the segmentation process. Special attention has not been paid to a modified system in which a more accurate segmentation process is applied to an already existing efficient algorithm thereby increasing the overall reliability and accuracy of iris recognition. In this work an improvement of the already existing wavelet packet decomposition for iris recognition with a Correct Classification Rate (CCR) of 98.375% is proposed. It involves changing the segmentation technique used for this implementation from the integro-differential operator approach (John Daugman’s model) to the Hough transform (Wilde’s model). This research extensively compared the two segmentation …
学术搜索中的文章
K Okokpujie, E Noma-Osaghae, S John, A Ajulibe - IT Convergence and Security 2017: Volume 2, 2018