High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
IEEE Transactions on Circuits and Systems for Video Technology
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An iris recognition method based on two-dimensional weighted principal component analysis (2DWPCA) and adaptive artificial neural network is proposed. As different iris region contains different recognition information, different weighting value is allocated to different region after compensating illumination intensity of the image in preprocessing. The two-dimensional principal component analysis is used to calculate the weighted subspace. And then 2DWPCA is utilized to extract the feature. Adaptive artificial neural network is employed to train and recognize the generated feature vectors. Owing to the 2DPCA features optimization of 2DPCA extraction and the self-adaption of neural network, the recognition ratio and robustness were greatly improved.