This article describes the design of an optical system using multi-wavelength illumination and dispersion principle to achieve iris recognition imaging with a large depth of field in noncooperative environments. Through the use of optical design software, the iris acquisition imaging system was designed with the modulation transfer function (MTF) curve serving as the evaluation criteria for this system. It was found that at different object distances, the MTF value at a spatial frequency of 100 lp/mm is greater than 0.33, indicating that the iris acquisition imaging system has a significant depth of field. To further validate the performance of the system, we set up an actual optical platform based on the parameters designed by the optical design software for the iris acquisition imaging system and conducted iris image acquisition experiments at different object distances, obtaining iris images of three different individuals. We performed algorithm verification on the iris recognition of the three sets of iris images and found that the average interclass matching result was 0.44, while the average intraclass matching result was 0.30, demonstrating a high level of accuracy in iris recognition. This indicates that the iris images obtained by the system have a high resolution, thereby confirming the feasibility of depth extension using multi-wavelength illumination and lens chromatic aberration imaging principle. It is worth mentioning that this method is not only applicable to iris recognition but also holds reference value in other biometric recognition fields.
Locating the pupil circle is an important step in iris recognition. As the light shines on the pupil, a bright reflection spot is formed in the iris image. In the process of iris location using Hough transform, location accuracy will be affected, because the reflection spot cannot be eliminated in practical optical system. Therefore, we proposed an algorithm to eliminate the reflected light spot in the pupil. The average gray value of the iris image can be obtained by using the gray histogram of the iris image. Then convolution of iris image with summation matrix of ten by ten is obtained, and the sum of gray values is less than a hundred times the average gray value and the approximate position of pupil can be found out. The pupil position is used to get the1 approximate position of the reflected highlight spot. The threshold is set to average threshold plus 128, and the point in the pupil field that is larger than the threshold can be obtained, and the position of the reflection point can be determined. The positions of the spot are set to zero. Using the algorithm, the number of highlight point in the binary iris image is reduced effectively. Thus Hough circle location would get higher location accuracy.
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