Du Yingzi, Arslanturk Emrah, Zhou Zhi, Belcher Craig
Biometrics and Pattern Recognition Laboratory, Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University–Purdue University Indianapolis, Indianapolis, IN 46202, USA.
IEEE Trans Syst Man Cybern B Cybern. 2011 Feb;41(1):64-74. doi: 10.1109/TSMCB.2010.2045371. Epub 2010 Apr 15.
In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.
在本文中，我们提出了一种基于视频的非合作虹膜图像分割方案，该方案纳入了一个质量过滤器以快速消除无眼睛的图像，采用了从粗到细的分割方案来提高整体效率，使用椭圆的直接最小二乘拟合方法对变形的瞳孔和边缘边界进行建模，并开发了一种基于窗口梯度的方法来去除虹膜区域中的噪声。搭建了一个远程虹膜采集系统来收集非合作虹膜视频图像。使用一种客观方法对分割结果的准确性进行定量评估。实验结果证明了该方法的有效性。所提出的方法将使非合作虹膜识别或虹膜监测成为可能。
