An kind of iris recognition algorithm based on 2D-PLDA and wavelet subband
一种基于2D-PLDA和小波子带的虹膜识别算法

In the last few years linear Discriminant Analysis(LDA)become more popular.But small sample size problem(SSSP) is always the biggest problem to perform it.In order to overcome this shortcoming,2D-LDA is proposed. We improve 2D-PLDA by Pre-Clustering,which can make the distribution matrix precisely;then a new iris recognition arithmetic is proposed which is combined with 2D-PLDA and wavelet transform.In the experiment,preprocessing was performed at first,then we extract the feature vector from the known class sample by 2D-PLDA and wavelet.In the validation step,we use Euclidean distance and Hamming distance to find the K-nearest neighbor to decide which class the unknown sample belongs to.From the experiment result,we can conclude that,the proposed arithmetic can achieve higher recognition rate than traditional LDA and 2D-LDA, also the new arithmetic is simple in calculation. We use the different subbands as the input space of 2D-PLDA,so the robustness is enhanced.