High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A region-based Iris feature extraction method based on 2D-wavelet transform
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Iris recognition using artificial neural networks
Expert Systems with Applications: An International Journal
Gait verification using knee acceleration signals
Expert Systems with Applications: An International Journal
Iris localization in frontal eye images for less constrained iris recognition systems
Digital Signal Processing
A review of information fusion techniques employed in iris recognition systems
International Journal of Advanced Intelligence Paradigms
Iris recognition using combined support vector machine and Hamming distance approach
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In this paper, a novel iris feature extraction technique with intelligent classifier is proposed for high performance iris recognition. We use one dimensional circular profile to represent iris features. The reduced and significant features afterward are extracted by Sobel operator and 1-D wavelet transform. So as to improve the accuracy, this paper combines probabilistic neural network (PNN) and particle swarm optimization (PSO) for an optimized PNN classifier model. A comparative experiment of existing methods for iris recognition is evaluated on CASIA iris image databases. The experimental results reveal the proposed algorithm provides superior performance in iris recognition.