利用序列图像解算目标视线角速率的方法

针对目标跟踪处理系统中的视线角速率提取问题,提出一种利用单成像探测器所得序列图像求导视线角速率的方法。利用序列图像中的运动目标图像坐标解算得到体视线角,通过图像匹配得到弹体姿态角,进而求解得到视线角速率。实验结果表明:结合图像跟踪算法可实时得到体视线角,使用图像匹配可以较好地解算得到弹体姿态角,解算结果误差小于5%;在体视线角和弹体姿态角均包含噪声的前提下,使用卡尔曼滤波可以较好地还原视线角速率。该方法适用于微小型飞行器制导探测,可以省去陀螺仪等惯性元件,实现探测装置的轻量化、小型化,具有实际的应用价值。     

一种基于椭圆投影的非理想虹膜定位算法

人以正常步行速度通过采集装置会出现非理想的虹膜图像.本文针对非理想虹膜中的角度偏离图像,提出了一种基于椭圆投影的虹膜定位算法.该算法首先计算双眼相对位置来决定头部的旋转角度,之后找到瞳孔内一点,从该点出发根据梯度变化搜索到虹膜的内边界点,采用最小二乘法拟合椭圆形内边界.然后依据椭圆与圆形的近似度检测人眼凝视方向,使用投...     

基于边缘增强引导滤波的光场全聚焦图像融合

受光场相机微透镜几何标定精度的影响,4D光场在角度方向上的解码误差会造成积分后的重聚焦图像边缘信息损失,从而降低全聚焦图像融合的精度。该文提出一种基于边缘增强引导滤波的光场全聚焦图像融合算法,通过对光场数字重聚焦得到的多幅重聚焦图像进行多尺度分解、特征层决策图引导滤波优化来获得最终全聚焦图像。与传统融合算法相比,该方法对4D光场标定误差带来的边缘信息损失进行了补偿,在重聚焦图像多尺度分解过程中增加了边缘层的提取来实现图像高频信息增强,并建立多尺度图像评价模型实现边缘层引导滤波参数优化,可获得更高质量的光场全聚焦图像。实验结果表明,在不明显降低融合图像与原始图像相似性的前提下,该方法可有效提高全聚焦图像的边缘强度和感知清晰度。     

眼轴及眼前节SS-OCT一体化成像系统

针对现有眼轴测量仪器无法同时实现大量程眼轴测量及眼前节成像的功能,设计了眼轴和眼前节同步测量的大量程扫频光学相干层析成像系统。该系统通过设计大量程扫频光源增加成像深度,并在外部设计搭建标定光路进行k域重采样以提高大量程干涉范围内的成像质量,从而在获取高精度眼轴信息的同时对眼前节成像;针对该系统OCT图像信噪比较低的问题,文中采用基于各向异性滤波的保边去噪算法对图像中的散斑噪声进行抑制以提高图像对比度。系统分别使用等比例人眼模型和离体鱼眼进行成像实验,实验结果表明:该系统成像深度可达到69 mm,在精准测量眼轴纵向五层结构的同时完成12 mm范围内的眼前节横向扫描,眼轴长度平均测量误差0.04 mm,成像时间约为0.45 s,满足临床医学应用中实时性的要求。     

A real-time focusing algorithm for iris recognition camera

For fast iris recognition, it is very important to capture the user's focused eye image at fast speed. Previous researchers have used the focusing method which has been applied to general landscape scenes without considering the characteristics of the iris image. So, they take much focusing time, especially in the case of the user with glasses. To overcome such problems, we propose a new iris image acquisition method to capture focused eye images at very fast speed based on corneal specular reflection. Experimental results show that the focusing time for both users with and without glasses averages 480 ms, and we conclude that our method can be used for the real-time iris recognition camera.     

基于虹膜参数提取的人眼注视方向识别算法

为了获得高精度的视线估算,提出了基于人眼虹膜参数提取和神经网络方法的视线方向估箅方法.首先利用中心投影成像,给出视线方向的初步估计;然后引入描述眼球运动的平动向量和转动向量,并利用人工神经网络对平动和转动引起的视线估算误差进行修正,有效地提高了人眼视线方向判断的精度.实验表明,测试样本组的视线估算精度达到了0.8°,明...     

基于图像处理的颗粒流动层模型研究

如何方便且准确地测量滚筒中颗粒的运动速率分布是研究的难点。文中将给出一种基于数字图像处理算法的实验方法来解决此难题。通过找到最合适的极短曝光时间,可捕获在此曝光时间内颗粒运动轨迹的图像,然后利用数字图像处理算法计算出感兴趣区域的颗粒运动路程,即可计算出颗粒的运动速率分布。通过精确的实验数据分析可看出,本实验方法与理论仅有＜8%的误差,有力证实了通过图像法测量颗粒速率分布可展开有效的研究工作。     

基于灰度投影的快速电子稳像算法

提出的基于灰度投影的快速电子稳像算法是将两维图像转化为一维投影曲线,然后进行一维相关运算求出运动矢量,因此计算量小速度快,且算法是对灰度图像进行直接处理,处理的信息反映了图像的整体特征并有效地抑制了噪声,因此具有较高的稳像精度.该算法经试验证明具有较好的稳像效果,并已进行了基于FPGA的硬件实现.     

Light field all-in-focus image fusion based on spatially-guided angular information

Compared to traditional 2D images, light field images record both spatial and angular information of the scene, which can provide more data for image fusion. In this paper, a light field all-in-focus image fusion algorithm based on spatially-guided angular information is proposed. In the proposed method, the initial weight maps carrying the angular information are calculated by comparing the block variance of the 4D light field data. The initial weight maps are then guided by digital refocused images carrying the spatial information to obtain the refined weight maps. In the refocused image multi-scale decomposition, the micro-lens calibration error is considered and the additional edge layers are extracted to suppress the edge artifacts. Experiments demonstrate the effectiveness of the proposed algorithm. Quantitative evaluation results show that the proposed algorithm performs the best in the feature-based index and structural similarity-based index without sacrificing the information and perceptual sharpness of the fused image.     

一种新颖的基于小波变换的虹膜识别算法

虹膜识别是一种新兴的生物识别技术,研究了虹膜图像的快速定位、增强等预处理方法,并提出了一种新颖的基于二维小波变换的虹膜识别算法,它的基本思想是：对预处理得到的虹膜图像进行四层小波分解,对得到的低频和高频系数抽取115维特征矢量,最后用汉明距离进行图像匹配判决合法性。实验证明,该算法运算速度较快,在图像模糊、噪声干扰等不利条件下仍具有良好的稳健性。     

互相关算法在运动目标距离选通激光三维成像中的应用

在微光成像中,距离选通成像是一种获取目标三维信息的有效手段。对于静止目标而言,可以通过对目标切片成像,获得不同选通距离的目标图像,进而通过二值化算法或质心算法获得目标的三维图像。而对于运动目标而言,在切片成像的同时,目标的空间位置会发生变化,因此需要对不同选通距离的目标图像进行配准,而后才能获得目标的三维图像。搭建了基于像增强电荷耦合器件(ICCD)的距离选通实验系统,提出了一种基于像质评价的互信息配准算法配准激光图像目标的空间位置,然后对配准后的激光图像通过互相关算法获得三维图像,并在保证一定的三维精度基础上,逐渐减少激光图像的像幅数,最后与二值化算法和质心算法三维重构进行了实验对比,实验结果表明,互信息配准算法能够有效配准激光图像,互相关三维成像算法精度高于二值化法和质心法,最少采用2幅图像即可获得目标的三维点云图像,大大降低了对运动目标三维成像的难度。     

A comprehensive multimodal eye recognition

Iris recognition is tested to be one of the most reliable approaches for automatic personal recognition under the infrared light. However, it is challenging and difficult to acquire good quality iris patterns of dark color eyes in the visible wavelengths. Sclera recognition can achieve good recognition accuracy in the visible spectrum, but the performance will drop when the sclera pattern is saturated. In this paper, we proposed a comprehensive multimodal eye recognition system that uses both iris and sclera patterns for recognition from the same eye image. The experimental results show that the proposed multimodal frontal eye recognition method can achieve better recognition accuracy than unimodal iris or sclera recognition. In addition, we propose a multimodal multi-angle eye recognition system that can further improve the recognition accuracy.     

一种结合人眼对比度感知特性的彩色图像压缩算法

为了使图像压缩后的效果更加符合人眼感知特性,提出了一种结合人眼对比度敏感视觉特性的图像压缩算法。算法首先结合视觉特性和图像变换域频谱系数特征,提出一种图像的角频率的计算方法,并依据计算的角频率提出一种人眼觉察图像最小误差阈值的计算方法;然后以此阈值作为量化步长,提出一种图像变换域频谱系数的量化方法;最后采用霍夫曼编码算法进行编解码,实现图像的压缩。并对三幅彩色图像进行了仿真实验,结果表明:与JPEG技术相比,三幅彩色图和各分量图的平均压缩比、PSNR和SSIM依次提高了10.4807%、6.9879%和2.6494%。表明提出的结合人眼视觉特性的图像压缩算法是一种较好的、有实用价值的压缩算法。     

Deformable model of the human iris for measuring ocular torsionfrom video images

The authors describe a deformable model of the human iris, which forms part of a system for accurate offline measurement of binocular eye movements, particularly cyclotorsion (torsion), from video image sequences. At least two existing systems measure torsion from infrared video images by pupil tracking followed by cross-correlation of bandpass filtered iris sectors. Unfortunately, pupil expansion and contraction reduce the accuracy of this method. In addition, infrared iris images typically contain very little texture, so correlation can be unreliable. A five-parameter deformable model was therefore developed for taken in visible light. This model can translate (horizontal and vertical eye motion), rotate (torsion) and scale both uniformly and radially (pupil changes). A series of software simulations and hardware tests suggest that torsion measurements obtained with the model are repeatable and accurate to within 0.1°. This performance is illustrated by analysing binocular torsion during fixation on a static target; the results match previously published data from other equipment     

基于区域候选孪生网络的红外目标跟踪算法

目标跟踪是光电设备的基本功能。为了应对跟踪任务中目标快速运动、复杂背景干扰以及遮挡的影响,不同于传统生成式方法与核相关滤波方法,本文提出一种使用深度学习的红外目标跟踪算法,使用双分支孪生特征提取网络对输入进行空间映射,经锚框划分图像区块后,分流为区域候选网络的“分类”与“回归”分支并进行特征模板匹配,对每个锚框进行分数评价后取“分类”分支中的最佳锚框,经“回归”分支进行预测边界回归后确定目标跟踪预测框,得到一种可以达到实时要求的红外单光宏观单目标跟踪算法。这种方法能够通过完全离线端到端训练整体系统参数获得,其制作过程简单,只要方法得当地进行参数精调,其性能有充分潜力可供挖掘。     

基于微粒子群优化算法的数字散斑图像相关方法

为了能够通过一步搜索同时得到数字散斑图像中所测点的整像素和亚像素位移信息,采用灰度插值的方法构造了亚像素子区,改进了基于微粒子群算法的数字图像散斑相关方法。对含有平移信息的模拟散斑图和具有应变的模拟散斑图进行相关计算,验证了该方法的适用性;在对具有微小面内位移转动的试件进行测量时,比较了整像素的微粒子群算法和不同量级的灰度插值下的亚像素微粒子群算法。结果表明,基于微粒子群算法的亚像素数字散斑图像相关方法在测量小位移方面具有一定的优越性。     

光学元件损伤暗场图像中的目标自动提取研究

基于光学元件损伤暗场成像图像的特点以及每个像素与周边的梯度关系,选择灰度——梯度对共生矩阵为研究模型,该模型集中反映了损伤图像中两种最基本的要素——灰度信息和梯度信息(边缘)。利用该模型产生准则函数,在信息论中最大熵原理基础上,应用文中改进的二维最大熵算法能自动确定最佳分割阈值,实现了对暗场图像的分割。该算法能够准确的从光学元件损伤暗场图像中提取损伤目标,为目标识别、精确定位和损伤大小的精确计算等后续处理提供依据。为了验证该算法,试验中对多个光学元件损伤暗场图像进行了处理分析,试验表明,该算法分割得到的损伤目标与实际相符,误差在检测的范围之内,为大型光学系统中光学元件损伤的在线、自动化检测提供了一种有效的技术途径。     

基于虹膜图像特征的噪声检测方法

在虹膜识别系统中,采集得到的图像,除了虹膜信息外,一般还会存在睫毛、眼睑及光源的像点等干扰.这会对虹膜的边界定位和特征提取产生影响,并最终导致识别率降低.通过对眼睑、睫毛、光斑噪声检测的研究,根据噪声的特点,提出一种新的快速定位眼睑的方法,并对双阈值检测睫毛的方法进行改进.试验结果表明,该方法能有效去除虹膜区域噪声干扰,提高识别率.     

Shoulder and elbow joint angle tracking with inertial sensors

Wearable inertial systems have recently been used to track human movement in and outside of the laboratory. Continuous monitoring of human movement can provide valuable information relevant to individuals' level of physical activity and functional ability. Traditionally, orientation has been calculated by integrating the angular velocity from gyroscopes. However, a small drift in the measured velocity leads to increasing integration error over time. To compensate that drift, complementary data from accelerometers are normally fused into tracking systems using the Kalman or extended Kalman filter. In this study, we combine kinematic models designed for control of robotic arms with state-space methods to continuously estimate the angles of human shoulder and elbow using two wearable inertial measurement units. We use the unscented Kalman filter to implement the nonlinear state-space inertial tracker. Shoulder and elbow joint angles obtained from 8 subjects using our inertial tracker were compared to the angles obtained from an optical-tracking reference system. On average, there was an RMS angle error of less than 8 (°) for all shoulder and elbow angles. The average correlation coefficient for all movement tasks among all subjects was r ≥ 0.95 . This agreement between our inertial tracker and the optical reference system was obtained for both regular and fast-speed movement of the arm. The same method can be used to track movement of other joints.