| Iris recognition refers to the use of human iris in the eyes of the identity of the identification of a technology;it has gained more and more attention in the recent years.Due to its high identification performance,the Iriscode,proposed by Daugman,is widely used in iris recognition systems.With the emphasis on biosafety security,how to reconstruct the iris image from Iriscode to judge the safety of iris recognition system has become a research hotspot.Due to the high dimension of the reconstructed image,using the iterative method to search the optimal solution in the high-dimensional space is inefficient,and the time complexity is high.In order to solve this problem this paper analyzes the problem of reconstructing iris images from Iriscode,proposes a reconstruction optimization model,and proposes a two-stage fast iris reconstruction algorithm.We regard the process of extracting Iriscode as the dimensionality reduction process.In the first stage,some inexact iris reconstruction images are reconstructed according to the neighborhood of the given Iriscode using locally linear embedding algorithm.In the second stage,we use the particle swarm optimization algorithm and the inexact iris images obtained in the previous stages as the initial particle to perform the iterative search to search the accurate result.Finally,the reconstructed rectangular iris image will be re-transformed into a ring and embedded into the human eye image to synthesize a complete human eye image.The innovations of the paper are as follows:(1)A reconstructed optimization model is proposed for reconstructing iris image from Iriscode;(2)A two-stage fast iris reconstruction method is proposed.Experiments show that the reconstructed iris images obtained by the proposed algorithm can achieve the purpose of forging attack through the iris recognition system.Compared to other reconstruction algorithms,there is an increase in time consuming and accept rate of the reconstructed image. |
PDF Full Text Request