Personal identification technique based on human iris recognition with wavelet transform

This paper presents a biometric recognition system, based on the iris of a human eye, using a wavelet transform. The proposed system includes three modules: image preprocessing, feature extraction, and recognition. The feature extraction module adopts the gradient direction (i.e., angle) of the wavelet transform as the discriminating texture features. The system encodes the features to generate its iris feature codes using two efficient coding techniques: binary Gray encoding and delta modulation. Experimental results show that recognition rates up to 95.27%, 95.62%, 96.21%, and 99.05%, respectively, using different coding methods, can be achieved.