Probability analysis of position errors using uncooled IR stereo camera

This paper analyzes the random phenomenon of 3D positions when tracking moving objects using the infrared (IR) stereo camera, and proposes a probability model of 3D positions. The proposed probability model integrates two random error phenomena. One is the pixel quantization error which is caused by discrete sampling pixels in estimating disparity values of stereo camera. The other is the timing jitter which results from the irregular acquisition-timing in the uncooled IR cameras. This paper derives a probability distribution function by combining jitter model with pixel quantization error. To verify the proposed probability function of 3D positions, the experiments on tracking fast moving objects are performed using IR stereo camera system. The 3D depths of moving object are estimated by stereo matching, and be compared with the ground truth obtained by laser scanner system. According to the experiments, the 3D depths of moving object are estimated within the statistically reliable range which is well derived by the proposed probability distribution. It is expected that the proposed probability model of 3D positions can be applied to various IR stereo camera systems that deal with fast moving objects.     

Infrared moving object detection based on local saliency and sparse representation

The key issue of infrared object detection is to locate moving object in image sequence. In order to improve detection precision, an infrared object detection method based on local saliency and sparse representation is proposed in this paper. Motion information, such as velocity, acceleration components are added into the eigenvectors to build local saliency model. And the approximate position of the infrared target is located based on the local saliency. To accurately extract the infrared object, sparse representation is used to capture complete edge of the object. Experiments show that the proposed method can accurately detect infrared moving objects, and has good robustness to external disturbances and dynamic background.     

Transillumination Laser Computed Tomography System with Fiber-Optic-Based Coherent Detection Imaging Method - High Spatial-Resolution and Quantitative Tomographic Imaging of Highly Scattering Objects -

We recently proposed and developed a novel transillumination laser computed tomography (CT) imaging system using a fiber-optic method based on coherent detection imaging (CDI) for biomedical use. Use of optical fibers enables portability and robustness against environmental changes in a room, such as variable temperature, air-flow shifts, and unexpected vibrations. In addition, motion-artifact-free images can be obtained because measurements can be performed with the object fixed. In the present paper, we experimentally investigate in detail the fundamental imaging properties of the system, which has a spatial resolution of 500 μm, a dynamic range of approximately 120 dB, and a minimum-detectable-optical power of 10⁻¹⁴W as a result of the excellent properties of the heterodyne detection. Based on experimental observations, the proposed system can reconstruct tomographic images of highly scattering objects in the transillumination mode, similar to X-ray CT, at sub-millimeter spatial resolution and with quantitativeness. Finally, we demonstrate with experiments using a physical phantom that the imaging system possesses high resolution and quantitative imaging abilities for highly scattering objects.     

全光纤激光多普勒测振仪空气耦合振动检测

采用外差探测方式, 建立了全光纤结构的激光多普勒测振仪,用来测量经空气传播耦合引起的散射体振动,以期感知振源振动信息。实验探索了散射体材料、固定方式和相对振源位置等对空气耦合振动的影响,得到了200~2700 Hz频率范围内6种散射体振动响应特性曲线。结果表明:通过空气耦合引起的散射体振动,在相同振源振幅下,散射体振动的振幅一般随频率升高而升高; 在材料、固定方式和相对振源位置等因素中,散射体材料对振动响应特性的影响是主要的,后两者只影响局部细节。     

多特征融合匹配的多目标跟踪

针对复杂背景的视频图像多目标跟踪遮挡问题,提出了一种多特征融合匹配的多目标跟踪方法。基于自适应高斯混合背景模型重构和更新背景策略,实现当前帧背景减除和多目标检测;采用目标的颜色特征、质心位置、运动速度等特征进行融合匹配跟踪;最后,通过区域辅助判定策略将场景下的目标状态分为目标进入场景、目标退出场景、目标暂消、目标重现、目标融合和分裂5种状态,用质心预测方法和遮挡因子辅助匹配来提高匹配正确率。仿真实验结果表明：采用该方法跟踪同一目标和不同目标的相似度平均值分别为0.949 71和0.505 73,优于单一颜色特征信息匹配;目标遮挡结束后重新匹配相似度为0.972 83,实现了复杂背景下具有表面相似性的多目标实时跟踪。     

A real-time,full-field,and low-cost velocity sensing approach for linear motion using fringe projection techniques

A velocity sensing approach using the fringe projection technique is presented. The moving object is projected with a sinusoidal fringe pattern. A CCD camera located at a different view angle observes the projected fringes on the dynamic object. The long exposure time of the CCD camera makes the fringes blurred by linear motion. The blurred fringes provide additional information to describe the depth displacement, and therefore the velocity vector can be identified. There is no need to take multiple-shot measurements to address the change in 3D positions at a sequence of time. Only one-shot measurement is required. Consequently, there is no need to perform image registration. The full-field approach also makes it possible to simultaneously inspect several objects.     

超声阵列方法在层状结构损伤检测中的应用*

层状钢筋混凝土结构常见的裂缝、层间离缝等损伤具有尺度小、隐蔽的特点,常规检测方法无法对其精确查明与定量评价。以高铁层状无砟轨道结构为研究对象,使用阵列式超声装备采集半矩阵数据,利用全聚焦算法对轨道内部结构及损伤成像,通过线性旅行时插值射线追踪算法计算超声波在层状介质中传播的最短到达时间代入全聚焦成像公式,具有深度准确、分辨率高、聚焦性好的特点。提出一种层间密实度评价方法,以表面超声直达波能量为基准分析反射波能量差异计算密实指数,可定量分析无砟轨道层间状态。文中层状介质的检测和层间损伤定量评价方法有效查明层状无砟轨道层内裂缝和层间离缝,对使用超声波检测层状结构及层间损伤具有借鉴意义。     

透过散射介质对直线运动目标的全光成像及追踪技术

光散射是限制光传输以及降低和破坏光学成像性能的主要因素,透过复杂散射介质对运动目标的全光成像是光学领域极具挑战性的技术之一.本文提出一种利用散斑差值自相关透过散射介质对运动目标进行实时追踪的方法.采用赝热光照明,基于光学记忆效应理论,通过对运动目标采集的两帧散斑做差值,然后做自相关运算,计算目标移动的距离,实现对目标的实时追踪,并且利用相位恢复算法进行简单处理就可以重建隐藏目标.对该方法进行了实验验证,成功地对隐藏的运动目标实现了成像与追踪.这种透过散射介质对运动目标的全光成像及实时追踪技术,在生物医学等领域具有重要应用潜力.     

采用多投影器的反向条纹投影技术

提出运用多投影器同时投影的反向条纹投影技术。通过测量标准样品的绝对相位,为不同角度放置的投影器产生不同的反向条纹。检测时,投影器同时投影各自的反向条纹,若物体和样品一致,在摄像机上就得到一幅消除了阴影和截断的标准正弦条纹图,若物体有变形,仅用裸眼就能判断,用简单的傅里叶变换和相位展开就能定量地描述变形。对于复杂的不连续物体也只需获取一幅条纹图就能完成检测,在很大程度上解决了阴影及相位展开的问题,实现了该类物体的在线快速检测。阐述了该技术的原理,以双投影器的反向条纹投影为例,实验验证了提出方法的有效性,并进行了相应的误差分析和应用条件讨论。     

Automatic Detection and Counting of Blood Cells in Smear Images Using RetinaNet

A complete blood count is one of the significant clinical tests that evaluates overall human health and provides relevant information for disease diagnosis. The conventional strategies of blood cell counting include manual counting as well as counting using the hemocytometer and are tedious and time-consuming tasks. This research-based paper proposes an automatic software-based alternative method to count blood cells accurately using the RetinaNet deep learning network, which is used to recognize and classify objects in microscopic images. After training, the network automatically recognizes and counts red blood cells, white blood cells, and platelets. We tested a model trained on smear images and found that the trained model has generalized capabilities. We assessed the quality of detection and cell counting using performance measures, such as accuracy, sensitivity, precision, and F1-score. Moreover, we studied the dependence of the confidence thresholds and the number of learning epochs on the obtained results of recognition and counting. We compared the performance of the proposed approach with those obtained by other authors who dealt with the subject of cell counting and show that object detection and labeling can be an additional advantage in the task of counting objects.     

Multi-scroll hidden attractors and multi-wing hidden attractors in a 5-dimensional memristive system

A novel 5-dimensional(5D) memristive chaotic system is proposed, in which multi-scroll hidden attractors and multiwing hidden attractors can be observed on different phase planes. The dynamical system has multiple lines of equilibria or no equilibrium when the system parameters are appropriately selected, and the multi-scroll hidden attractors and multi-wing hidden attractors have nothing to do with the system equilibria. Particularly, the numbers of multi-scroll hidden attractors and multi-wing hidden attractors are sensitive to the transient simulation time and the initial values. Dynamical properties of the system, such as phase plane, time series, frequency spectra, Lyapunov exponent, and Poincar′e map, are studied in detail. In addition, a state feedback controller is designed to select multiple hidden attractors within a long enough simulation time. Finally, an electronic circuit is realized in Pspice, and the experimental results are in agreement with the numerical ones.     

结合区域提取和改进卷积神经网络的水下小目标检测

针对水下小目标信息量有限而难以提取有效特征导致的检测性能不佳问题,提出了一种结合区域提取和融合Hu矩特征的改进卷积神经网络水下小目标检测方法。该方法包含区域提取和分类两个步骤。首先以马尔可夫随机场分割算法为基础进行区域提取,对潜在目标定位的同时降低伪目标对后续分类的干扰;然后提取潜在目标区域的Hu矩特征并融入卷积神经网络,形成一种形状特征表征能力更强的改进卷积神经网络用于分类。声呐实测数据处理结果表明,该方法可以有效提升对水下小目标的发现概率和正确报警率,与其他目标检测方法相比,该方法具有更好的检测性能和泛化性。     

基于随机背景建模的目标检测算法

运动目标检测是智能视频监控系统中的重要步骤和前提。提出了一种基于随机背景建模的非参数化建模算法,对场景中运动目标进行快速提取跟踪。在初始化阶段,从当前像素的邻域中随机抽取样本值作为背景模型;在模型更新阶段,引入了随机更新策略和背景传播机制,能够较好地抑制环境噪声;在后处理阶段,给出了一种基于积分图的前景滤波优化方法,进一步滤除噪声和填充前景空洞。实验结果表明,在复杂场景条件下,算法的目标检测性能明显优于其他几种同类算法,能够较好地抑制噪声干扰,具有较高的检测正确率。对于360288像素的测试视频,算法的计算速度高达120 f/s,完全可以满足实时应用。     

快速消除车辆阴影的多阈值图像分割法

 视频图像分割时的运动阴影由于与被测对象的相似性而常被误判为被测对象,传统的阴影检测方法一般难以满足实时智能交通系统对处理速度的要求。为此,提出用多阈值法分割图像,将灰度化的当前图像与背景差分,再用正、负两个阈值对其二值化,在分割出深色和浅色被测对象的同时消除阴影。实验表明,将这种方法应用于运动车辆的检测,具有速度快和阴影消除效果好等特点,可应用于实时的运动目标检测和跟踪等领域。     

动态背景下基于光流场分析的运动目标检测算法

针对现有动态背景下运动目标检测算法的不足,提出一种基于光流场分析的运动目标检测算法.首先根据前背景在光流梯度幅值和光流矢量方向上的差异确定目标的大致边界,然后通过点在多边形内部原理获得边界内部的稀疏像素点,最后以超像素为节点,利用混合高斯模型拟合的表观信息和超像素的时空邻域关系构建马尔可夫随机场模型的能量函数,并通过使目标函数能量最小化得到最终的运动目标检测结果.该算法不需要任何先验假设,能够同时处理动态背景和静态背景两种情况.多组实验结果表明,本文算法在检测的准确性和处理速度上均优于现有算法.     

集成成像大纵深物体的三维形貌获取技术

为了满足现代工业所需的大纵深物体的三维形貌获取需求,解决传统结构光三维形貌获取技术纵深较小的问题, 借助集成成像这种阵列式多视点获取技术,构建了基于集成成像的大纵深物体的三维形貌获取技术。从集成成像原理出发,分析了集成成像三维物点和同名像点之间的关系,得到集成成像光学获取系统参数和三维物体纵深极限之间的关系。在此基础上,利用相机和电动平移台构建了扫描式相机集成成像三维形貌获取系统,并对纵深从600 mm到3 600 mm相对独立的2个物体构建的大纵深三维物体进行了形貌获取。光学实验结果显示,该集成成像大纵深物体三维形貌获取技术能够单次获取纵深为3 600 mm的三维物体的三维形貌,为大纵深物体的三维形貌获取提供了技术支持。     

Finding community structures in complex networks using mixed integer optimisation

The detection of community structure has been used to reveal the relationships between individual objects and their groupings in networks. This paper presents a mathematical programming approach to identify the optimal community structures in complex networks based on the maximisation of a network modularity metric for partitioning a network into modules. The overall problem is formulated as a mixed integer quadratic programming (MIQP) model, which can then be solved to global optimality using standard optimisation software. The solution procedure is further enhanced by developing special symmetry-breaking constraints to eliminate equivalent solutions. It is shown that additional features such as minimum/maximum module size and balancing among modules can easily be incorporated in the model. The applicability of the proposed optimisation-based approach is demonstrated by four examples. Comparative results with other approaches from the literature show that the proposed methodology has superior performance while global optimum is guaranteed.     

一种具有隐藏吸引子的分数阶混沌系统的动力学分析及有限时间同步

对于具有隐藏吸引子的混沌系统,既有文献大多只针对整数阶系统进行分析与控制研究.基于Sprott E系统,构建了仅有一个稳定平衡点的分数阶混沌系统,通过相位图、Poincare映射和功率谱等,分析了该系统的基本动力学特征.结果显示,该系统展现出了丰富而复杂的动力学特性,且通过随阶次变化的分岔图可知,系统在不同阶次下呈现出周期运动、倍周期运动和混沌运动等状态,这些动力学特征对于保密通信等实际工程领域有重要的研究价值.针对该具有隐藏吸引子的分数阶系统,应用分数阶系统有限时间稳定性理论设计控制器,对系统进行有限时间同步控制,并通过数值仿真验证了其有效性.     

基于大数据分析的移动对象轨迹预测方法

对移动对象的轨迹预测将在移动目标跟踪识别中具有较好的应用价值。移动对象轨迹预测的基础是移动目标运动参量的采集和估计,移动目标的运动参量信息特征规模较大,传统的单分量时间序列分析方法难以实现准确的参量估计和轨迹预测。提出一种基于大数据多传感信息融合跟踪的移动对象轨迹预测算法。首先进行移动目标对象进行轨迹跟踪的控制对象描述和约束参量分析,对轨迹预测的大规模运动参量信息进行信息融合和自正整定性控制,通过大数据分析方法实现对移动对象运动参量的准确估计和检测,由此指导移动对象轨迹的准确预测,提高预测精度。仿真结果表明,采用该算法进行移动对象的运动参量估计和轨迹预测的精度较高,自适应性能较强,稳健性较好,相关的指标性能优于传统方法。     

Homodyne and heterodyne imaging through a scattering medium

We introduce a novel two-dimensional (2D) homodyne and heterodyne technique for imaging objects through or embedded in a scattering medium. Our imaging approach is based on heterodyning of light with different Doppler broadenings that is scattered from objects of two different textures or from an opaque object and a textured scattering medium. We report on the initial demonstration of pulling signals out of noise for an object hidden behind a scattering medium. Enhancements of signal-to-noise ratio of the order of 50 have been achieved by use of a 2D holographic phase-sensitive detector. We also discuss the experimental feasibility of this approach for objects embedded in a scattering medium.