Research On The Technology Of Iris Image Processing And Encoding

With the development of information technology in contemporary society, the demands for security are becoming more and more important. As the important member in this area, iris recognition can be performed widely in the application future and has wide market development future, but in our country it is just on the beginning.Iris localization is an important part of iris recognition system. Its speed and precision affect the system performance significantly. By researching the old algorithm, a two-step method of arc fitting using segmented edges is proposed to detect the inner circles of iris, and comparison experiment with the algorithm in existence. The test experiment shows that the proposed method is robust, efficient and practical.In order to ensure high recognition rate and remove the disturbing factor in iris recognition, and analyze different noise in the iris field and take several of the methods to eliminate the noise. On the base of the algorithm of a two-step method of arc fitting using segmented edges, succeed in removing the noise affection of the eyelid. Experimental results show that the approach is helpful to improve pattern classification effect and recognition reliability. Make use of gray value threshold method to remove eyelash and facula noise in iris image. An iris image revise module is built in this article which revises some deviation including in shift, rotate, scale zoom. In the iris recognition system, the quality of iris image is important factor to affect the recognition rate, on the base of iris image quality evaluation module in existence, a synthetical iris image quality evaluation is proposed by considering the main factors which may cause failure. Experimental results show that the approach can be consistent with the subjective experience approach on image qualityGabor filter can simulate the figure of receptive field in mammiferous optokinetic neurons well. 2D Gabor function do well in uniting localization and direction selection in space and frequency fields, so it is very fit for extracting the iris texture. The algorithm of extracting the iris texture by 2D Gabor filter is the best method in existence. In this article, 2D Gabor filter is researched deeply and is used to code iris characteristics. The experimental results are given.It is the new way to apply the nonlinear dimension reduction to the image recognition, the Laplician Eigenmap nonlinear dimension reduction is tried to code the iris characteristics in this article, and the experimental results are analyzed by the statistics theory, which shows that it is feasible.