Iris recognition based on improved empirical mode decomposition method
Yuefang Dong · Journal of Jilin University · 2013
An iris recognition method based on improved empirical mode decomposition is proposed.First,the normalized iris image is decomposed based by row and then column to generate the different layer intrinsic mode components of the image.Second,the feature image is obtained by binarizing the components useful for the iris recognition.Third,the Hamming distance matching vector is obtained by horizontal and vertical shift match.Finally,the improved standard deviation of the matching vector is calculated,which is used as the threshold for iris recognition.This method is tested using CASIA1,CASIA2,CASIA3-Interval and MMU1 databases.Experiment results show that this method can extract the binary feature effectively,with faster speed and higher correct recognition rate.