微透镜阵列实现3维物体旋转不变实时识别

为了实现3维物体旋转不变实时识别,应用微透镜阵列的多视角成像特点,利用透射像阵列的高关联性,实现3维物体信息与2维透射像阵列信息之间的转换,从而可以利用光学2维图像识别技术实现3维物体的识别.对转换和识别过程进行了理论分析,用匹配滤波的方法进行了实验验证,实现了3维物体旋转不变实时识别.得到了良好的识别效果,并实现了旋转方向的准确定位和旋转角度大小的比较判别.结果表明,应用微透镜阵列可以实现旋转3维物体旋转不变实时识别.     

集成成像系统实现三维物体旋转不变分类识别

提出一种基于集成成像系统和综合判别函数(SDF)实现三维物体旋转不变分类识别的新方法。方法利用集成成像系统获取旋转三维物体的单元像阵列图像,应用图像中各个单元像记录的三维物体信息之间的高关联特性,结合SDF,实现了三维物体的旋转不变分类识别。与已有方法相比,本文方法减小了识别过程的数据量,降低运算复杂度,提高了识别效率,且不受物体旋转角度的限制。针对多类旋转三维物体,利用本文方法实现了旋转不变分类识别,验证了方法的有效性。     

旋转不变的三维物体识别

提出一种具有旋转不变性的三维物体识别的新方法。该方法通过结构照明的方法,使物体的高度分布以变形条纹的形式编码于二维强度像中。由于条纹图像包含有物体的高度分布信息,因而对条纹图的相关识别具有本征三维识别的特点。旋转不变性是通过使用多通道滤波器实现的,此滤波器可以由不同方向三维物体对应的变形条纹图像经计算机处理得到。相关识别方法可以用光学匹配空间滤波器实现。计算机模拟实验证明了这种方法的有效性,它不仅可以实现旋转不变的三维物体识别,还可以给出物体旋转角度的估计值。     

一种基于集成成像生成计算全息图的方法

提出了一种基于集成成像生成三维(3D)物体计算全息图的方法。利用微透镜阵列获取微图像阵列,通过像素提取获得正交投影子图像阵列,根据3D中心切片理论,将各正交投影子图像的二维(2D)傅里叶频谱放入相对应的3D傅里叶空间中,提取其相交的部分并叠加,可以获得3D物体在透镜后焦面的频谱信息分布。计算出在一定传播距离处的菲涅耳衍射分布,用全息编码方法生成菲涅耳计算全息图。进行模拟再现,给出在不同再现距离上获得的再现像,验证了该方法的可行性。该方法能够在非相干光照明的情况下采用3D傅里叶频谱制作真实3D物体的全息图,它减小了系统的复杂程度,在算法实现上更加简单。     

用于提高集成成像景深的微透镜阵列研究

集成成像3D显示是一种运用微透镜阵列从不同方 位对三维物体记录和重构的真三维显 示技术,针对集成成像3D显示技术景深不够、微透镜之间间隙透过的杂散光引起干扰导致的 重构图像质下降等问题,本文设计新型微透镜阵列结构(双层针孔/微透镜组合阵列结构)以 减少杂散光并增加集成成像3D显示的中心深度平面的个数以提高集成成像的景深。根据集成 成像原理,确定双层针孔/微透镜组合阵列的参数,利用Tracepro光学仿真软件对集成成像3D显示过程进 行仿真,结果表明,双层针孔/微透镜组合阵列能有效地较少杂散光;当两层微 透镜阵列间距为5mm时,本文系统获得的景深比传统系统大20 mm左 右,即 双层针孔/微透镜组合阵列结构能够实现在减少杂散光影响的同时又增加集成成像的景深。     

基于3DS MAX的集成成像研究

集成成像(II)是一种利用二维微透镜阵列进行三维信息的记录和重现的技术.介绍了集成成像技术的基本原理及其优缺点,提出了一种基于三维设计和动画制作软件3DsMAX的II技术,利用3DS MAX来实现II的三维信息的记录,利用显示器和菲涅尔微透镜阵列组成的实验装置实现II的三维信息的重现,解决了常规II技术存在的空间反转和串扰问题,从而研制出基于Il技术的原理性裸眼三维显示器.     

基于逆滤波器的旋转不变匹配滤波相关识别

提出了用逆滤波器来进行旋转不变匹配滤波相关识别方法 ;采用级联变形滤波器可以实现透射匹配相关峰强度对透射输入能量的优化 ,大大改善相关峰的锐度 ,计算机模拟结果显示 ,对旋转图像 ,在平面内按 0°～ 32°旋转 ,每 4°取一灰度图像的旋转不变匹配滤波相关器 ,具有较好的相关不变识别性能 ,特别是目标图像在部分输入情况下也能较好地识别     

基于ISAL的含旋转部件目标成像及微动特征提取

逆合成孔径激光雷达能实现对目标的高分辨2维成像,但如果目标中包含旋转部件,旋转部件回波带来的微多普勒效应会对目标的成像造成干扰。该文提出一种含旋转部件目标微多普勒特征提取及成像方法,首先利用匹配参考信号的方法对回波信号进行一定程度的非线性补偿,然后通过二值数学形态学方法提取频率-慢时间谱图中微多普勒特征曲线的信息,并利用微多普勒特征曲线的周期性进行曲线分离,实现对目标旋转部件微动参数的快速提取。在此基础上,对主体回波信号和旋转部件回波信号进行分离,完成对目标主体的2维成像。仿真实验验证了该文算法不仅能有效剔除目标旋转部件对逆合成孔径激光雷达成像的干扰,还能通过微多普勒特征的提取为目标识别提供新的途径。     

高填充因子微透镜阵列的快速制备及特性分析

微透镜阵列是一种被广泛应用于光信息处理、光传感、光计算、光通信和高灵敏度成像等领域的精密光学元器件之一。通过一些先进的制造技术已经可以制造出不同几何形状、轮廓和光学特性的微透镜阵列。然而,由于三维微制造工艺的难度,使得高填充因子微透镜阵列中的微透镜很难实现紧密排列。提出了一种快速、低成本的微流体操纵技术,用于制备高填充因子微透镜阵列,且对其制备工艺进行了初步的演示。这种易于操作的制造技术适用于微透镜阵列的大批量生产,极大地提高了生产效率。通过预先制备出的三种不同尺寸(微柱直径分别为300、500、700 μm)的微柱,实现了与其对应不同形状和尺寸的微透镜阵列的制备,并搭建了一套光学成像系统以对这些微透镜阵列进行成像性能的评估。主要对微透镜阵列的焦距、成像精度和每个微透镜阵列中各个微透镜子单元成像的均一性进行测试,利用所提出的微流体操控技术制备的微透镜阵列具有良好的成像性能,有望能够被应用到三维成像、光均匀化等诸多应用中。     

小视场集成成像三维信息获取技术研究

为了满足利用非接触式方法获取小 视场三维信息的要求, 研究了一种基于集成成像技术获取小视场三维信息的系统,并在借鉴传统微透镜阵列(MLA) 及相机阵列工作模式的基 础上,通过利用精密二维平移台,巧妙地将相机阵列应用于获取小视场三维信息中。系 统工作时,首先将相机 获取的图像合成元素图像阵列,并运用相应的算法实现三维重建与测量。实验结果表明,本 文系统获取了相对清晰、没有相互串扰的元素图像阵列,实现了完整且细节丰富的三维 图像再现;可以 获取待测物体上任意一点的三维坐标,并且三维测量误差保持在0.3 mm 以内。实验结果相对理想,为集成成像技术应用于高精密测量提供了理论基础。     

基于莫尔条纹的三维物体的旋转不变识别

本文提出一种基于莫尔条纹的三维物体旋转不变识别方法。采用阴影莫尔法的装置和频域滤波的方法,可得到物体的莫尔条纹图。因为物体的莫尔条纹是物体的等高线,体现三维物体特征的高度函数以莫尔等高线的形式编码于强度图中,因此基于莫尔条纹的相关识别具有本征三维识别的特点。采用振幅调制和功率谱相减的联合变换相关,用实现旋转不变识别的综合鉴别函数(SDF)作为联合变换相关输入的参考图像,来获得具有识别目标的旋转不变性和高的相关识别率。计算机模拟试验结果证明了这种方法用于三维物体旋转不变性识别的有效性。     

3-d object retrieval and recognition with hypergraph analysis

View-based 3-D object retrieval and recognition has become popular in practice, e.g., in computer aided design. It is difficult to precisely estimate the distance between two objects represented by multiple views. Thus, current view-based 3-D object retrieval and recognition methods may not perform well. In this paper, we propose a hypergraph analysis approach to address this problem by avoiding the estimation of the distance between objects. In particular, we construct multiple hypergraphs for a set of 3-D objects based on their 2-D views. In these hypergraphs, each vertex is an object, and each edge is a cluster of views. Therefore, an edge connects multiple vertices. We define the weight of each edge based on the similarities between any two views within the cluster. Retrieval and recognition are performed based on the hypergraphs. Therefore, our method can explore the higher order relationship among objects and does not use the distance between objects. We conduct experiments on the National Taiwan University 3-D model dataset and the ETH 3-D object collection. Experimental results demonstrate the effectiveness of the proposed method by comparing with the state-of-the-art methods.     

Automatic target recognition by matching oriented edge pixels

This paper describes techniques to perform efficient and accurate target recognition in difficult domains. In order to accurately model small, irregularly shaped targets, the target objects and images are represented by their edge maps, with a local orientation associated with each edge pixel. Three dimensional objects are modeled by a set of two-dimensional (2-D) views of the object. Translation, rotation, and scaling of the views are allowed to approximate full three-dimensional (3-D) motion of the object. A version of the Hausdorff measure that incorporates both location and orientation information is used to determine which positions of each object model are reported as possible target locations. These positions are determined efficiently through the examination of a hierarchical cell decomposition of the transformation space. This allows large volumes of the space to be pruned quickly. Additional techniques are used to decrease the computation time required by the method when matching is performed against a catalog of object models. The probability that this measure will yield a false alarm and efficient methods for estimating this probability at run time are considered in detail. This information can be used to maintain a low false alarm rate or to rank competing hypotheses based on their likelihood of being a false alarm. Finally, results of the system recognizing objects in infrared and intensity images are given.     

Similarity measure for superquadrics

Superquadrics with parametric deformations are suitable models for use as solid primitives for describing a complicated 3-D object. Some different methods for the recovery of superquadric primitives from range data have been proposed, but there is still no effective similarity measure for the matching task between two superquadrics in a 3-D object recognition system. The authors propose a similarity measure to evaluate the degree of shape similarity between two superquadric-based objects. This similarity measure is defined as the volume of regions bounded by the surfaces of two 3-D objects. The proposed measure has been proved to be a metric. The metric value is computed by the Monte Carlo integration method. The experimental results illustrate that the proposed similarity measure is effective in matching a recovered superquadric with a set of superquadrics in the model database     

The design of rotation-invariant pattern recognition using thesilicon retina

A new rotation-invariant pattern recognition system is proposed and analyzed. In this system, silicon retina cells capable of image sensing and edge extraction are used so that the system can directly process images from the real world without an extra edge detector. The rotation-invariant discrete correlation function is modified and implemented in the silicon retina structure by using the current summation. Simulation results have verified the correct function of the proposed system. Moreover, an experimental chip to implement the proposed system with a 32×32 cell array has been designed and fabricated in 0.8-μm n-well CMOS process. Experimental results have successfully shown that the system works well for the arbitrary orientation pattern recognition     

Camera constraint-free view-based 3-D object retrieval

Recently, extensive research efforts have been dedicated to view-based methods for 3-D object retrieval due to the highly discriminative property of multiviews for 3-D object representation. However, most of state-of-the-art approaches highly depend on their own camera array settings for capturing views of 3-D objects. In order to move toward a general framework for 3-D object retrieval without the limitation of camera array restriction, a camera constraint-free view-based (CCFV) 3-D object retrieval algorithm is proposed in this paper. In this framework, each object is represented by a free set of views, which means that these views can be captured from any direction without camera constraint. For each query object, we first cluster all query views to generate the view clusters, which are then used to build the query models. For a more accurate 3-D object comparison, a positive matching model and a negative matching model are individually trained using positive and negative matched samples, respectively. The CCFV model is generated on the basis of the query Gaussian models by combining the positive matching model and the negative matching model. The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database. We conduct experiments on the National Taiwan University 3-D model database and the ETH 3-D object database. Experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods.     

基于双L型阵的二维测向算法

提出了一种基于双L型阵的二维测向算法。通过定义新的三维波达方向角,同时利用旋转不变算法获得每一维入射角的独立估计,再由波达方向角之间的约束关系进行配对,提高了测向精度与二维角成功配对概率,改善了双L阵二维测向精度对来波方向敏感的问题。计算机仿真结果表明:所提算法在观测的区域内均具有较高测向精度,特别是在仰角较小时较传统算法其测向精度有较大提高,在低信噪比情况下与传统算法比较提高了二维测向中的角度配对成功概率。     

Validation of 3-D curved objects: CAD model and fabricatedworkpiece

This paper proposes a new method to describe and identify a 3-D curved object for the purpose of validating a fabricated object to the design specification. Curved 3-D objects are, in general, difficult to represent and identify because they lack distinct properties such as edges, planes, or cylindrical surfaces which are the building blocks in representing objects. In this paper, the authors propose to use principal axes of a 3-D object to establish a reference for the representation. A method of obtaining an inertia matrix from a 3-D range image is developed. The unique set of principal axes is obtained from the inertia matrix of an object with an arbitrary 3-D position and orientation, and the object can be described uniquely on these principal axes. On the principal axes, an object is described by a set of features describing the shape of the object such as spine, section size, section orientation, and section contraction. The features are used for comparing two objects for the validation purpose. The authors also propose a direct measure of similarity between two objects as a mean-squared difference of radii. As an experiment, two 3-D object models are designed through a CAD package, and fabricated objects are compared with the designed models for validation purposes     

Three-dimensional holographic image sensing and Integral imaging display

In this paper, we propose three-dimensional (3-D) holographic sensing, and computational/optical 3-D integral imaging reconstruction. We demonstrate experimentally that through the integral imaging technique, it is possible to reconstruct a full 3-D scene which has been obtained by digital holograms. Three-dimensional color objects can also be displayed optically in 3-D without convergence-accommodation conflict using a microlens array, and a two-dimensional (2-D) display panel illuminated by incoherent light. The proposed approach takes advantages of high resolution holographic sensing and robust 3-D integral imaging visualization.