Acquisition of Iris Images, Iris Localization, Normalization, and Quality Enhancement for Personal Identification
Iris based biometric personal identification and verification methods have gained much interest with an increasing emphasis on security. The proposed approach comprises of acquisition of iris images, iris localization, normalization and quality enhancement. Algorithms like circular hough transform, canny edge detection, gabor filters, homogeneous rubber sheet model, and daubechies wavelets methods were used based on the requirements of the Iris Image Processing (IIP) module. Accurate templates are the key to Iris recognition system. Artifacts removal and pre-processing will help to produce accurate matching patterns. The authors' proposed work produced 99.14% accuracy in edge detection, which gives reliable solution to the segmentation and quality enhancement.