The Research And Implementation Of Iris Recognition Algorithm

Iris recognition system has been an active research area in recent years as a result of the social and economical development, and it shows great advantages. For example, iris posses distinct features for uniquely identifying a person, the characteristics of one's iris are steady all one's life, can check whether is nature iris exactly, which prevents counterfeiting. The capturing of iris image is non-invasive, and so on.In this paper, a detail discussion of the two mature iris recognition systems, Daugman's and Wildes's, is carried out. We have done deeply research on iris recognition algorithm and implemented a detection system on work attendance. The researches are mainly focused on the improvement of iris sampling equipment, iris localization, the quality evaluation of iris image, live detection, coding and test statistic.A method using wavefront to extend the depth-of-field of the image capture system is expatiated in the paper. To use wavefront can reduce the sampling system's sensitivity to depth-of-field, which make the image sampled in the range of±15cm available for ID recognition.The iris localization is the key step for iris recognition, an improvement localization algorithm based on Daugman's algorithm is proposed, which is provided not only more efficient on localization speed, but also more effective on the performance than the famous Daugman's algorithm. To localize both upper and lower eyelid boundaries, the method used in this paper excludes directly the area of iris covered by the eyelid.For the quality evaluation of iris image, a new evaluation method is introduced. First, It detects if the iris is in the middle of the image, then evaluate the quality of localized iris part. This method has a effective quality evaluation of the iris image.With regard to the iris live detection, this paper proposed a method. It is done according to the pupil zoom, cornea and energy spectrum.Some improvements are made on Daugman's Gabor wavelet coding algorithm, we add an effectively flag in the pattern codes of every pixel, so the matching method is modified accordingly, To do the match operations only on the both effective pixels, which reduces the percentage of rejection recognition.A great deal of tests have been done on our algorithm, we statistic the percentage of wrong acceptance and wrong recognition, The test results are also presented and analyzed, which show the validity of our algorithms.In the end of this paper, the main problems to be solved for the current iris recognition system and the future research work to be done in this field are proposed.