Line segment Hausdorff distance on face matching

A novel concept of line segment Hausdorff distance is proposed in this paper. Researchers apply Hausdorff distance to measure the similarity of two point sets. It is extended here to match two sets of line segments. The new approach has the advantage to incorporate structural and spatial information to compute the similarity. The added information can conceptually provide more and better distinctive capability for recognition. This would strengthen and enhance the matching process of similar objects such as faces. The proposed technique has been applied online segments generated from the edge maps of faces with encouraging result that supports the concept experimentally. The results also implicate that line segments could provide sufficient information for face recognition. This might imply a new way for face coding and recognition.     

Moment-based methods for polygonal approximation of digitized curves

Object shape representation plays an important role in the area of image processing, pattern recognition and computer vision. In the past two decades, many algorithms have been suggested for creating approximated polygons. In this study, two new polygonal approximation methods based on the geometric moments and the orthogonal moments defined in terms of Legendre polynomials are proposed. The difference between the moments defined by the initial contour and those of the approximated polygon is taken as the objective function. Each algorithm provides various polygonal approximation results with different number of line segments for different application situations. For a given error bound, we can determine the optimal polygon with a minimum number of line segments. The procedures are applied to some digital curves and better results are obtained in comparison with some known methods.     

Human activity recognition using multi-features and multiple kernel learning

This paper presents two sets of features, shape representation and kinematic structure, for human activity recognition using a sequence of RGB-D images. The shape features are extracted using the depth information in the frequency domain via spherical harmonics representation. The other features include the motion of the 3D joint positions (i.e. the end points of the distal limb segments) in the human body. Both sets of features are fused using the Multiple Kernel Learning (MKL) technique at the kernel level for human activity recognition. Our experiments on three publicly available datasets demonstrate that the proposed features are robust for human activity recognition and particularly when there are similarities among the actions.     

Graph-based deformable matching of 3D line with application in protein fitting

We present an algorithm for matching two sets of line segments in 3D that have undergone non-rigid deformations. This problem is motivated by a biology application that seeks a correspondence between the alpha-helices from two proteins, so that matching helices have similar lengths and these can be aligned by some low-distortion deformation. While matching between two feature sets have been extensively studied, particularly for point features, matching line segments has received little attention so far. As typical in point-matching methods, we formulate a graph matching problem and solve it using continuous relaxation. We make two technical contributions. First, we propose a graph construction for undirected line segments such that the optimal matching between two graphs represents an as-rigid-as-possible deformation between the two sets of segments. Second, we propose a novel heuristic for discretizing the continuous solution in graph matching. Our heuristic can be applied to matching problems (such as ours) that are not amenable to certain heuristics, and it produces better solutions than those applicable heuristics. Our method is compared with a state-of-art method motivated by the same biological application and demonstrates improved accuracy.     

基于Voronoi图的线段反向最近邻查询

提出一种基于平面线段的反向最近邻查询方法,用于找出线段集中以查询线段作为最近邻的线段。通过构造线段集的Voronoi图处理不相交的线段。根据其邻接特性和局部特性,给出基于Voronoi图的线段反向最近邻查询算法及相关定理和证明。实验结果表明,反向最近邻方法易于找到相交的线段,具有较高的查询效率。     

基于多尺度轮廓段的形状特征提取与识别

形状识别是计算机视觉与模式识别领域的重要研究内容。形状的特征选取与描述是形状识别的研究热点。针对现有识别方法的不足，提出一种通过对不同长度轮廓段进行描述，进行特征提取的方法。对每个形状均在6种尺度下进行特征提取，每种尺度选取5种轮廓段特征参数，实现了对形状的特征描述。在形状识别阶段，使用动态时间规整（DTW）算法度量形状描述子之间的匹配距离，实现形状识别。分别在Kimia99、Kimia216和MPEG-7数据库中进行算法验证，结果表明基于多尺度轮廓段的形状特征描述子具有旋转、缩放、平移和局部遮挡不变性，识别率优于现有算法。     

基于直线段跟踪的手绘图元离线识别方法*

手绘图形是人类思维外化和表达意图的一种有效方式,如何有效地提取手绘在图纸上的图形元素是理解绘图者意图的关键问题。鉴于手绘图形是由基本图元组合构成,采用层次结构逐步实现图元提取的思想,提出了一种手绘基本图元（线段、弧、圆和椭圆）的离线识别方法。在提取图形笔画骨架像素的基础上,跟踪骨架像素得到图形的直线段描述;通过对直线段序列的分析,进行直线段序列的断开和连接处理,形成图元的曲线段描述,通过对图元曲线段描述的分析得出图元的几何参数。实验表明,该方法能够以高精确度快速识别出图像中包含的手绘图元,具有良好的稳定性     

Algorithms for matching 3D line sets

Matching two sets of lines is a basic tool that has applications in many computer vision problems such as scene registration, object recognition, motion estimation, and others. Line sets may be composed of infinitely long lines or finite length line segments. Depending on line lengths, three basic cases arise in matching sets of lines: 1) finite-finite, 2) finite-infinite, and 3) infinite-infinite. Case 2 has not been treated in the literature. For Cases 1 and 3, existing algorithms for matching 3D line sets are not completely satisfactory in that they either solve special situations, or give approximate solutions, or may not converge, or are not invariant with respect to coordinate system transforms. In this paper, we present new algorithms that solve exactly all three cases for the general situation. The algorithms are provably convergent and invariant to coordinate transforms. Experiments with synthetic and real 3D image data are reported.     

Hybrid two segments ring dielectric resonator antenna for ultrawideband application

In this article, a hybrid two segments ring dielectric resonator antenna with partial ground plane, for ultrawideband application is described. The proposed antenna structure consists of annular shape microstrip line along with two ring dielectric resonators having different permittivity. By applying the combination of shifted annular shape microstrip line (used as a radiator as well as to convert TM_01δ mode to TE_01δ mode) and two segments ring dielectric resonator, ultra wide bandwidth has been achieved. Prototype of proposed structure has been fabricated and tested. Measured results show good agreement with the simulated ones. The proposed antenna structure operates over a frequency range of 3.45‐10.9 GHz with a fractional bandwidth of 103.83% and having better gain and radiation characteristics. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:47–53, 2016.     

空间数据库中的线段k近邻查询研究

K近邻查询是空间数据库中的重要查询之一,k近邻查询在内容的相似性检索、模式识别、地理信息系统中有重要应用。针对现有k近邻查询都是基于点查询的情况,提出基于平面线段的k近邻查询,查找线段集中给定查询点的k个最近线段。给出基于Voronoi图的线段k近邻查询算法及给出相关定理和证明。该算法通过线段Voronoi图的邻接特性找到一个候选集,然后从中找到最终结果。通过随机数据的实验证明,所提算法明显优于线性扫描算法和基于R树的k近邻查询算法。     

Lexicon-driven segmentation and recognition of handwritten character strings for Japanese address reading

This paper describes a handwritten character string recognition system for Japanese mail address reading on a very large vocabulary. The address phrases are recognized as a whole because there is no extra space between words. The lexicon contains 111,349 address phrases, which are stored in a trie structure. In recognition, the text line image is matched with the lexicon entries (phrases) to obtain reliable segmentation and retrieve valid address phrases. The paper first introduces some effective techniques for text line image preprocessing and presegmentation. In presegmentation, the text line image is separated into primitive segments by connected component analysis and touching pattern splitting based on contour shape analysis. In lexicon matching, consecutive segments are dynamically combined into candidate character patterns. An accurate character classifier is embedded in lexicon matching to select characters matched with a candidate pattern from a dynamic category set. A beam search strategy is used to control the lexicon matching so as to achieve real-time recognition. In experiments on 3,589 live mail images, the proposed method achieved correct rate of 83.68 percent while the error rate is less than 1 percent.     

正则化最近点优化图像集匹配的三维人脸识别

针对传统的三维人脸识别算法受光照、表情、姿态及遮掩等变化而影响识别性能的问题,提出了一种基于正则化最近点优化图像集匹配算法。将图库图像集和探针图像集建模成正则化仿射包,利用迭代器自动确定两个图像集间的正则化最近点;利用最近子空间分类器最小化正则化最近点;根据正则化最近点之间的欧氏距离及结构计算RNP集之间的距离,利用最近邻分类器完成人脸的识别。在Honda/UCSD、BU4DFE两大视频人脸数据库上的实验验证了该算法的有效性及可靠性,实验结果表明,相比其他几种较为先进的三维人脸识别算法,该算法取得了更好的识别效果,同时,大大减少了训练及测试总完成时间。     

目标边界点集的层次化描述及其形状检索应用

提出用于轮廓线形状和区域形状图像检索的形状描述方法,该方法将目标形状的边界（包括内边界）表示为一个无序的点集,沿各方向对点集的迭代分割,建立层次化的边界点集描述模型.通过对各层形状边界的分割比和分散度的几何特征度量,产生各层的形状特征描述,对它们进行组合,建立对目标形状的层次化描述.两个目标形状的差异性度量定义为它们的层次化描述子的L-1距离.该方法具有：（1）通用性.能够描述轮廓线形状和区域形状这两种不同类型的形状;（2）可扩展性.基于所提出的分层描述框架,可以将分割比和分散度这两种几何度量进行扩展,纳入更多其他几何特征度量,以进一步提高形状描述的精度;（3）多尺度描述特性.提出的分层的描述机制,使得描述子具有内在的由粗到细的形状表征能力;（4）较低的计算复杂性.由于仅仅计算目标图像的边界像素点,使得算法具有较高的计算效率.用MPEG-7 CE-2区域形状图像库和MPEG-7 CE-1轮廓线形状图像库这两个标准测试集对该方法进行评估,并与同类的其他形状描述方法进行比较,实验结果表明：提出的方法在综合考虑检索精确率、检索效率和一般应用能力等指标的情况下,其性能上要优于各种参与比较的方法.     

用于形状识别的目标轮廓无序点集描述与匹配

将目标形状的轮廓看成一个无序的点集,从中抽取形状特征,用于快速而有效的目标识别是形状分析任务中的挑战性问题.针对该问题,提出了一种基于复杂网络模型的形状描述和识别方法.该方法提出用一种自组织的网络动态演化模型构成一个分层的描述框架,在网络动态演化的每一个时刻,对网络分别进行局部测量和全局测量,抽取网络的无权特征和加权特征.在形状匹配阶段,用获得的局部描述子和全局描述子分别进行局部匹配（基于Hausdorff距离）和全局匹配（基于L₁距离）,组合两种匹配的距离值构成对形状的差异度度量.用标准的测试集对所提出的方法进行性能测试,实验结果表明,所提出的算法能够快速而又鲁棒地完成较高精度的形状识别任务.     

一种笔段序列匹配联机汉字识别方法

文中针对行书体汉字的识别,提出一种笔段序列匹配汉字识别方法。选择笔段数、笔段书写顺序、笔段位置作为主要的识别特征。首先,在预处理阶段,为了减小汉字类内分散性,采用笔段密度均衡化非线性规整法对笔段位置进行了非线性规整;进而在笔段序列的基础上,采用动态规划算法寻找待识笔段序列与候选笔段序列的最优匹配路径;根据此路径,得到匹配笔段集,缺少笔段和多余笔段;然后计算出待识字与每个候选字的识别距离;最后,对识     

Robust and efficient detection of salient convex groups

This paper describes an algorithm that robustly locates salient convex collections of line segments in an image. The algorithm is guaranteed to find all convex sets of line segments in which the length of the gaps between segments is smaller than some fixed proportion of the total length of the lines. This enables the algorithm to find convex groups whose contours are partially occluded or missing due to noise. We give an expected case analysis of the algorithm performance. This demonstrates that salient convexity is unlikely to occur at random, and hence is a strong clue that grouped line segments reflect underlying structure in the scene. We also show that our algorithm run time is O(n ²log(n)+nm), when we wish to find the m most salient groups in an image with n line segments. We support this analysis with experiments on real data, and demonstrate the grouping system as part of a complete recognition system     

高斯卷积角:用于叶片图像检索的形状描述不变量

植物叶片图像的识别是计算机视觉和图像处理技术在生物学和现代农业中的一个重要应用.其挑战性在于植物叶片种类数量巨大,且许多叶片图像具有很大的类间相似性,使得描述叶片图像的类间差异变得非常困难.提出一种称为高斯卷积角的叶片形状描述方法.该方法用高斯函数与叶片轮廓点的左右邻域向量的卷积产生高斯卷积角,再通过改变高斯函数的尺度...