Automatic localization of pupil using eccentricity and iris using gradient based method

This paper presents a novel approach for the automatic localization of pupil and iris. Pupil and iris are nearly circular regions, which are surrounded by sclera, eyelids and eyelashes. The localization of both pupil and iris is extremely important in any iris recognition system. In the proposed algorithm pupil is localized using Eccentricity based Bisection method which looks for the region that has the highest probability of having pupil. While iris localization is carried out in two steps. In the first step, iris image is directionally segmented and a noise free region (region of interest) is extracted. In the second step, angular lines in the region of interest are extracted and the edge points of iris outer boundary are found through the gradient of these lines. The proposed method is tested on CASIA ver 1.0 and MMU Iris databases. Experimental results show that this method is comparatively accurate.     

基于特定感兴趣区采样的虹膜定位改进算法

从虹膜图像特点出发,以瞳孔形心为辅助点实现对虹膜图像特定感兴趣区采样.并且根据虹膜内外圆半径的生理特点设定Hough变换半径参量,依据虹膜内外圆近似同心圆来筛选与虹膜外圆最匹配的Hough变换结果.该算法在主动避开眼皮,睫毛干扰的同时又显著降低了Hough变换的计算量.通过对中科院自动化所CASIA虹膜数据库108组图像的虹膜定位测试结果表明,该方法平均定位时间0.83 s,定位准确率98.9%.     

Iris localization based on the Hough transform,a radial-gradient operator,and the gray-level intensity

The iris biometric recognizes a human based on his/her iris texture, which is a stable and unique feature for every individual. A typical iris biometric system performs better for the ideal data, which is acquired under controlled conditions. However, its performance degrades when localizing iris in non-ideal data containing the noisy issues, e.g., the non-uniform illumination, defocus, and non-circular iris boundaries. This study proposes a reliable algorithm to localize iris in such images robustly. First, a small region containing the coarse location of iris is localized. Next, the pupillary boundary is extracted within this small region using an iterative-scheme comprising an adaptive binarization and a pupil location verification test. Following that, the limbic boundary is localized by reusing the Hough accumulator. The iris location is also verified through a gray-level test. After that, the pupillary and limbic boundaries are regularized by applying an enhanced method comprising a Radial-gradient operator (RGO), an error-transform (ET), and the Fourier series. Experimental results, obtained on the CASIA-IrisV3, CASIA-IrisV4, MMU V1.0, and MMU(new) V2.0 iris databases, show superiority of the proposed technique over some of the contemporary techniques.     

Iris segmentation using variational level set method

Continuous efforts have been made to process degraded iris images for enhancement of the iris recognition performance in unconstrained situations. Recently, many researchers have focused on developing the iris segmentation techniques, which can deal with iris images in a non-cooperative environment where the probability of acquiring unideal iris images is very high due to gaze deviation, noise, blurring, and occlusion by eyelashes, eyelids, glasses, and hair. Although there have been many iris segmentation methods, most focus primarily on the accurate detection of iris images captured in a closely controlled environment. The novelty of this research effort is that we propose to apply a variational level set-based curve evolution scheme that uses a significantly larger time step to numerically solve the evolution partial differential equation (PDE) for segmentation of an unideal iris image accurately, and thereby, speeding up the curve evolution process drastically. The iris boundary represented by the variational level set may break and merge naturally during evolution, and thus, the topological changes are handled automatically. The proposed variational model is also robust against poor localization and weak iris/sclera boundaries. In order to solve the size irregularities occurring due to arbitrary shapes of the extracted iris/pupil regions, a simple method is applied based on connection of adjacent contour points. Furthermore, to reduce the noise effect, we apply a pixel-wise adaptive 2D Wiener filter. The verification and identification performance of the proposed scheme is validated on three challenging iris image datasets, namely, the ICE 2005, the WVU Unideal, and the UBIRIS Version 1.     

基于暗瞳图像的人眼视线估计

虹膜外边缘受眼睑遮挡较为严重时, 会给虹膜中心的准确提取造成很大的困难. 为此, 提出利用放置在相机轴外的红外光源产生的暗瞳图像估计瞳孔中心, 该方法避免了提取虹膜外边缘遇到的遮挡问题. 首先利用角膜反射光斑在相机像面中的位置估计角膜所在球体中心的三维空间坐标, 作为眼球的平动信息; 然后考察瞳孔中心与角膜球体中心在相机成像面投影位置的相对偏移, 作为眼球的转动信息; 最后利用人工神经网络完成视线特征向量与注视点坐标间的映射. 在人眼区域定位的问题上, 利用两部大视场相机, 采用自适应增强算法和主动表观模型算法实现眼部区域的准确定位, 该步骤可以将提取反射光斑和瞳孔中心需要考虑的图像区域限定在较小的范围内. 实验结果表明, 本文视线估计方法在水平方向上的平均误差为0.62°, 在竖直方向上的平均误差为1.05°, 是解决视线点估计的有效方法. 关键词： 暗瞳 人工神经网络 自适应增强 主动表观模型     

A non-circular iris localization algorithm using image projection function and gray level statistics

Iris recognition technology identifies an individual from its iris texture with great precision. A typical iris recognition system comprises eye image acquisition, iris segmentation, feature extraction, and matching. However, the system precision greatly depends on accurate iris localization in the segmentation module. In this paper, we propose a reliable iris localization algorithm. First, we locate a coarse eye location in an eye image using integral projection function (IPF). Next, we localize the pupillary boundary in a sub image using a reliable technique based on the histogram-bisection, image statistics, eccentricity, and object geometry. After that, we localize the limbic boundary using a robust scheme based on the radial gradients and an error distance transform. Finally, we regularize the actual iris boundaries using active contours. The proposed algorithm is tested on public iris databases: MMU V1.0, CASIA-IrisV1, and the CASIA-IrisV3-Lamp. Experimental results demonstrate superiority of the proposed algorithm over some of the contemporary techniques.     

Iris segmentation for visible wavelength and near infrared eye images

State-of-the-art iris segmentation algorithms exhibit poor performance for non-ideal data, which is mainly because of the noise such as low contrast, non-uniform illumination, reflections, and among others. To address this issue, a robust iris segmentation scheme is proposed that includes the following: First, a set of the Seed-pixels in a preprocessed eye image is marked adaptively. Next, a two-fold scheme based on a Circu-differential accumulator (CDA) and gray statistics is adopted to localize coarse iris region robustly. Notably, the proposed CDA has close resemblance with the Hough transform; however, it consumes relatively less memory and is free from thresholding as well. Similarly, pupillary boundary is localized, which is verified through an intensity test as well. Next, a refine estimate for the limbic boundary is extracted. After that, iris boundaries are regularized using the Fourier series. Finally, the eyelids are localized using a Para-differential accumulator (PDA), and eyelashes and reflections are also localized adaptively in the polar form of iris. Experimental results on the near infrared (NIR) and visible wavelength (VW) iris databases show that the proposed technique outperforms contemporary approaches.     

基于人眼灰度分布特征的虹膜定位算法

虹膜定位是虹膜识别过程中的重要环节,定位速度和精度决定了整个虹膜识别系统的性能。提出了一种基于人眼灰度分布特征的虹膜定位算法,该算法利用形态学运算实现瞳孔圆心粗定位,采用划分区域求灰度均值隔项差值最大值的方法实现外圆半径的粗定位,并通过分层聚类的方法实现内外边界的精确定位。实验结果表明．与经典的虹膜定位算法如Wildes算法、Daugman算法相比,该算法定位结果更加准确,定位速度大幅度提高。     

一种新的激光光斑参数快速计算方法

提出了一种利用弦的特性快速提取激光光斑参数的二维Hough变换方法。基本步骤是在圆形光斑边缘图像上作两条交于边缘上一点且相互垂直并分别平行于坐标轴的弦,通过这两条弦与光斑圆心及半径的几何关系,求取光斑的中心坐标和半径。遍历所有边缘点,对参数空间二维中心坐标数组投票,最大值对应参数即为光斑中心坐标。分析一维归一化半径直方图,求得光斑半径。实验结果表明,与传统的Hough变换相比,该算法在运行时间和空间效率上都有很大提高,具有更强的实用意义及应用前景。     

光瞳半径对纯位相调制激光束整形系统的影响

光瞳截断作用对纯位相调制激光束整形系统的系统性能有重要影响. 本文提出了一种关于光瞳半径对近场调制位相和远场系统评价函数影响的定量分析方法. 通过拉格朗日乘数法等方法分析光瞳半径对近场调制位相的影响, 结果表明: 近场调制位相随光瞳半径近似线性增加. 通过建立数学模型, 拟合分析光瞳半径对系统评价函数的影响. 结果表明: 对方形目标光强, 系统评价函数拟合精度确定系数达到99%左右, 光瞳半径为2.5倍高斯光束束腰半径时, 相关系数达到0.997, 光强偏离残差平方均值达到0.0004左右, 光瞳截断作用趋于最小; 对圆形目标光强, 系统评价函数拟合精度确定系数达到97%, 光瞳半径为3倍高斯光束束腰半径时, 相关系数与光强偏离残差平方均值变化幅度均在10^-3量级, 系统评价函数趋于收敛, 光瞳截断作用趋于最小.     

特定边界跟踪中角点检测研究

针对边界跟踪算法中在角点附近丢失边界信息的问题,对待检测边界中角点的判别和检测方法进行了研究。分析了边界搜索中所扩展的邻域的半径和角点位置的关系,提出了角点存在判据,给出了角点存在区间。提出了寻区间法角点检测算法,用5个已知边界点之间的关系,判断出角点存在的邻域,通过选取合适的邻域半径,使角点存在区间向角点收敛。对测试图像和人侧面轮廓图像的边界利用所提出的算法进行跟踪,测试图像的边界点从19个增长为37个,人侧面轮廓图像边界点从13个增长为21个,新算法准确地检测到轮廓角点和后续种子点,使边界跟踪能够反映所有的边界信息。     

光学小波包变换及其滤波器的研究

基于对光学小波变换必要条件的分析,提出光学小波包变换的概念.选出虹膜图库的联合最优小波包基,利用最优基的线性组合生成相应的复合光学小波包滤波器.将滤波器用于光电混合虹膜识别系统中对待识别输入进行小波包特征提取预处理,模拟结果不仅证明引入该滤波器可明显提升系统的识别效果,也证明了光学小波包变换提出的意义.     

一种新颖的智能眼镜光学系统设计方法

提出采用Fresnel微结构的曲面波导微投影光学系统眼镜设计思想,理论分析了所提光学系统的成像原理,给出了光学设计方法,并运用该方法设计了一套样机,曲面波导板近眼表面(即前表面)曲率半径为140.0 mm,后表面曲率半径为143.5 mm,中心厚度为1.7 mm,材料选PMMA (即有机玻璃),微型显示器选0.23″硅基OLED显示屏,分辨率640×480(象素),出瞳直径选为8 mm,眼点距约为18 mm,视场角9.6°(H)×7.2°(V),调制传递函数(MTF)在空间分辨率30 lp/mm时,中心视场MTF接近0.45,全视场大于0.2。从而验证了该方法的可行性。     

基于介质环形柱结构的二维光子晶体中Dirac点的实现

利用偶然简并方法在二维正方格子介质环形柱结构光子晶体中成功实现了Dirac点, 并利用平面波展开法对实现Dirac点的过程进行了研究. 研究结果表明, 对于二维正方格子介质环形柱结构光子晶体, 在一定的外径R_O范围内(0.37a<R_O<0.5a), 当Dirac点存在时(n>1.4), 介质环内径R_I与外径R_O满足一个不随介质环折射率n变化的恒定关系式. 同时, Dirac点对应的光子约化频率f随折射率n及外径R_O的增大而减小. 利用所得的关系式对特定介质环折射率n条件下能实现Dirac点的环形光子晶体进行了预判设计.     

Strain distribution and electronic structures of the InAs/GaAs quantum ring molecule in an applied electric field

The strain distribution and electronic structures of the InAs/GaAs quantum ring molecule are calculated via the finite element method.In our model,three identical InAs quantum rings are aligned vertically and embedded in the cubic GaAs barrier.Considering the band edge modification induced by the strain,the electronic ground state and the dependence of ground state energy on geometric parameters of the quantum ring molecule are investigated.The change of localization of the wavefunction resulting from the applied electric field along the growth direction is observed.The ground state energy decreases as the electric field intensity increases in a parabolic-like mode.The electric field changes the monotonic dependence of the energy level on the inter-ring distance into a non-monotonic one.However,the electric field has no effect on the relationships between the energy level and other geometric parameters such as the inner radius and outer radius.     

基于环形微腔的多频段三角晶格光子晶体耦合腔波导光学传输特性

本文理论研究了近红外波段硅基三角晶格光子晶体环形微腔的光场局域特性,通过将微腔在空间周期性排列组成耦合腔光波导,研究了多个导带区域内光束传输时的群速度,最大和最小值分别为0.0028c和0.00028c.将环形微腔在垂直于光传输方向上进行交错排列,通过改变相邻微腔之间的耦合区域,可以大幅降低多频段范围内光束在耦合腔波导中传输时群速度之间的差异,并提高部分频段的透过率数值.在不改变介质柱半径条件下,通过去掉三角晶格光子晶体中距中心介质柱距离分别为2a和√3a的六个介质柱构成了两种微腔,研究了两种微腔所支持的谐振波长之间的差异,在此基础上构造了两种耦合腔波导,进而将这两种耦合腔光波导与W1型输入/输出波导相连,最终实现了在多个不同频率范围内降低群速度的同时实现频段选择和频段分束功能,其导模群速度可降低到0.00047c.     

利用可变光阑实现双轴晶体动态外锥折射

介绍了一种获得晶体动态外锥折射的方法.用全固态绿光激光器和双轴晶体kNbO_3,通过改变位于已消球差的双胶合透镜后表面处可变光阑的通光孔径,即改变入射光束的会聚角度,来实现入射光会聚角对外锥折射锥角的调制,由此得出双轴晶体kNbO_3外锥折射的锥角表达式.实验结果表明,周期性改变孔径光阑通光孔径的大小(入射光束的会聚角度)时,外锥折射锥角也同步地发生周期性的改变;外锥折射锥角等于入射于双轴晶体端面上的光线的会聚角.利用可变光阑可实现双轴晶体动态外锥折射并获得可控激光环,实验所测锥角角度与理论计算符合较好.     

The Piecewise Two Points Autolinear Correlated Correction Method for Fourier Transform Infrared Baseline Wander

Baseline wander always blurring or even deteriorating analytical results, it is necessary to correct in order to perform further data analysis. Several correction algorithms have been proved to have some effect on this correction. However, these methods require user intervention or may be complicated and time-consuming. A novel algorithm named the autolinear correlated correction basing on piecewise was proposed. This method first divided the raw spectrum into different regions according to no absorption or nonsensitive bands which had very low or no sensitivity to target gases. And then spectrum lines were selected in every band and their means were calculated. Spectrum lines which were closest to the average were selected as the band center. According to the algorithm, the parameters of constant and autocorrelation coefficient were calculated within each band. Finally, baseline was corrected by the determined parameters. Experimental results on real spectrum demonstrated the effectiveness and high efficiency of the algorithm, making it suitable for the fully automated and online baseline correction.     

Eye pupil detection system using an ensemble of regression forest and fast radial symmetry transform with a near infrared camera

In this paper, we focus on pupil center detection in various video sequences that include head poses and changes in illumination. To detect the pupil center, we first find four eye landmarks in each eye by using cascade local regression based on a regression forest. Based on the rough location of the pupil, a fast radial symmetric transform is applied using the previously found pupil location to rearrange the fine pupil center. As the final step, the pupil displacement is estimated between the previous frame and the current frame to maintain the level of accuracy against a false locating result occurring in a particular frame. We generated a new face dataset, called Keimyung University pupil detection (KMUPD), with infrared camera. The proposed method was successfully applied to the KMUPD dataset, and the results indicate that its pupil center detection capability is better than that of other methods and with a shorter processing time.