An Efficient Technique for Online Iris Image Compression and Personal Identification

In this research article, an iris image compression and identification algorithm called Iris Image Compressor and Identifier is proposed which will convert the iris image of eye in the form of Laplace–Beltrami Spectra. Further, this Laplace–Beltrami Spectra will be converted into the form of Strakos matrix, and for these matrices the Eigen values are calculated which will be enough to identify a person. These Eigen values will be stored in the smart card memory for further identification and compression. Therefore, for checking whether two iris images are isometric or not, it is required to compare the first “n” Eigen values of the iris image spectra. If two iris images have the same Eigen values or same Riemannian Metrics values then it shows that both the irises are belonging to the same person. If two iris images have different Eigen values or different Riemannian Metrics values then it means that both the irises are belonging to different persons. We conducted the experiments for one hundred iris images of CASIA database. The robustness testing was conducted by modifying few pixels in specific regions and few pixels in overall image. But still the proposed method was able to identify individuals on the basis of their iris image patterns. The results of iris implementation reveal that the proposed method is an efficient and economically feasible.