A Research On The Methods For The Extraction Of Human Iris Feature

Iris recognition is a highly efficient way of biometrics. An automatically capturing iris system and image quality appreciation is introduced. The iris image of high quality is then filtered by median value. A value threshold is found from the iris histogram to separate the pupil area. And after the continuous area detection, the eyelashes noise is eradicated. The pupil is located in a way searching coarsely the pixel, in whose line and column the total pixels value sum is maximal. And then integral-differential operator precisely determine the inner center. In order to decrease noise disturbance, according to the inner parameter, Daugman's area integral calculus is adopted to detect the iris outer boundary.Iris normalization mapped the iris area to a normalization rectangle. In this paper, iris normalization is done by using the real pupil marginal pixel instead of the inner marginal pixel of iris location, the new method efficiently wiped off the macula and preserved the original information of the iris area. By analyzing the effect of location parameter to iris normalization, find out that a new method which integrates iris coarse location, iris outer edge location and the new normalization arithmetic increases the program rate. After the normalization of the iris area,2-D optimized Gabor transform and zero crossing are performed, after which the image is dealt with mathematic morphology method to remove noise.In this paper, the iris feature extraction and encoding is done by 2D wavelet transform and coefficients zero-crossing. In contrast to Daugman's algorithm, both memory and time are saved.