基于p2-不变量的透视变换下的点模式匹配方法

点模式匹配是计算机视觉和模式识别领域中的一个重要问题 .通过研究 ,在假定待匹配的两个点模式中已知有三对点整体对应的前提下 ,基于射影坐标以及对投影变换和排序变换同时保持不变的 p2 -不变量等理论 ,通过定义一种广义距离 ,给出了一种求解透视变换下 ,点数不等的两个平面点模式匹配问题的新算法 .理论分析和仿真实验表明 ,该算法是快速、有效的     

基于凸壳的透视变换下的点模式匹配方法

1　引言点模式匹配是计算机视觉和模式识别领域中的一个重要课题 .它的主要任务是 ,将满足一定几何变换关系的同一场景的两幅图像中的点 ,进行匹配成对 ,从而识别和定位物体 .它适用于解决基于光学传感器的应用中的许多问题 ,如图像配准、物体识别、目标跟踪、自主导航和姿态测定等 .鉴于透视变换下点集匹配问题的复杂性 ,有些研究者对问题作了某种近似和简化 ,如 :当物体的大小和物体与相机的距离相比可忽略不计时 ,相机成像的透视变换可用仿射变换来有效近似[1 ,2 ] .但这种假设在许多实际应用中是难以成立的 (文献 [3 ]中专门研究了用仿…     

基于空间透视不变量的摄旬有机标定方法

本文给出了一种以空间不变量的数据来计算摄象机外部参数的方法。空间透视不变量是指在几何变换中如投影或改变观察时保持不变的形状描述。     

基于双灭点的图像透视变换方法

对监控场景中目标的精确定位,需要进行图像坐标系与世界坐标系之间的转换。而在实际应用中,由于安装因素等原因,难以获取摄像机的图像坐标系与世界坐标系之间转换的参数。提出一种基于双灭点的图像透视校正方法。通过分析世界坐标系中4个控制点在图像坐标系中的位置关系,实现透视投影下图像坐标系与世界坐标系之间的转换。实验结果证明该方法简便实用。     

基于空间透视不变量的摄象机标定方法

本文给出了一种以空间不变量的数据来计算摄象机外部参数的方法．空间透视不变量是指在几何变换中如投影或改变观察点时保持不变的形状描述．由于它可以得到一个相对于外界来讲独立的物体景物的特征描述，故可以很广泛的应用到计算机视觉等方面．摄象机标定是确定摄象机摄取的２Ｄ图象信息及其３Ｄ实际景物的信息之间的变换关系，它包括内部参数和外部参数两个部分．内部参数表征的是摄象机的内部特征和光学特征参数，包括图象中心（Ｃｘ，Ｃｙ）坐标、图象尺度因子Ｓｘ、有效的焦距长度ｆ和透镜的畸变失真系数Ｋ；外部参数表示的是摄象机的位置和方向在世界坐标中的坐标参数，它包括平移矩阵Ｔ和旋转矩阵Ｒ３×３，一般情况下可以写成一个扩展矩阵［ＲＴ］３×４．本文基于空间透视不变量的计算数据，给出了一种标定摄象机外部参数的方法，实验结果表明该方法具有很强的鲁棒性．     

基于目标不变量的识别方法研究

一、引言不变量理论在80年代末引入计算机视觉领域,1991年召开了不变量在计算机视觉应用方面的国际研讨会。目前,对这一课题的研究引起了国内外学者的极大兴趣。视觉不变量理论的优点在于它对目标形状的描述不受目标物体的姿态、透视投影和摄像机内部参数的影响。同时它可以冗余地表示目标全局结构特征,当发生部分遮挡时,可以从剩余部分计算出表示全局的结构不变信息。     

一种基于极坐标变换的点模式匹配算法

点模式匹配是目标识别、图像配准与匹配、姿态估计等计算机视觉与模式识别应用方向的基础问题之一。提出了一种新的利用点特征进行匹配的算法,该算法根据点集的分布与点位置信息,构建了点的特征属性图,通过极坐标变换得到对数极坐标的特征图,并利用几何不变矩方法对特征图进行描述。由特征描述向量的比较,获得粗匹配结果,然后通过几何约束迭代的方法获取最终的点集匹配结果。本文贡献如下:一,构建了一种点的极坐标变换特征,并运用不变矩进行描述,使所提特征具有旋转与平移的不变性;二,提出了利用点特征与整体点集几何约束结合的匹配算法,能有效克服出格点与噪声带来的不利影响。最终实验说明了算法的有效性和鲁棒性。     

一个基于代数不变量的目标识别算法

首先给出了用于代数不变量的“参照系”和“坐标”的概念,然后给出了一个基于代数不变量进行目标识别的算法,最后给出了算法的实验结果。     

轮廓矩不变量及其在物体形状识别中的应用

为了有效地刻画物体的形状特征,在基于区域的Hu矩不变量的基础上,构造了一种基于物体轮廓曲线的新的矩不变量,即轮廓矩不变量。该不变量不仅独立于物体本身的颜色和灰度级,而且具有平移、旋转和尺度不变性,因此可将轮廓矩不变量应用于物体形状的识别,为了能快速地进行物体形状识别,还讨论了小波边缘检测和轮廓的获取问题及其算法。实验表明,基于这种轮廓矩的识别算法具有很好的识别率。     

一种基于投影不变量的目标跟踪方法

提出了一种基于平面投影不变量的目标跟踪算法．算法从图像中提取直线边缘计算投影不变量,用于对目标建模并跟踪．为提取直线边缘,使用改进的序列细化算法将边缘细化为单像素宽,而后用一种快速曲率估计方法估算边缘点的曲率,并保留估算值很小（约等于零）的点拟合直线．在所得直线族中按照邻近规则或者窗口规则挑选直线计算投影不变量．图像处理实验给出了用文中提出的图像预处理算法获得的直线边缘效果,并通过使用所得直线计算不变量的值衡量了所得不变量的稳定性和视角不变性．跟踪实验检验了跟踪算法的鲁棒性和实用性．     

Retrieval of images of man-made structures based on projective invariance

In this paper we propose a geometry-based image retrieval scheme that makes use of projectively invariant features. Cross-ratio (CR) is an invariant feature under projective transformations for collinear points. We compute the CRs of point sets in quadruplets and the CR histogram is used as the feature for retrieval purposes. Being a geometric feature, it allows us to retrieve similar images irrespective of view point and illumination changes. We can retrieve the same building even if the facade has undergone a fresh coat of paints! Color and textural features can also be included, if desired. Experimental results show a favorably very good retrieval accuracy when tested on an image database of size 4000. The method is very effective in retrieving images having man-made objects rich in polygonal structures like buildings, rail tracks, etc.     

Homogeneous coordinates

This paper presents an overview of homogeneous coordinates in their relation to computer graphics. A brief historical review is given, followed by the introduction of the homogeneous coordinate system. We elucidate its application in two-dimensional Euclidean space. Particular attention is given to the subjects of affine transformations effected with matrix multiplication and the intersection of two-dimensional lines. Homogeneous coordinates in three dimensions and, in detail, perspective transformations are also discussed. A method for clipping lines with respect to the viewing frustum is provided.     

基于极坐标的树木叶片特征提取方法

提出了一种在极坐标下进行特征提取的方法,并将其应用于树木叶片图像识别中。该方法首先将目标图像二值化并映射到极坐标下,提取具有旋转、缩放、平移不变性的曲线面积比率、跨度比、饱和度和高度变化率等特征。然后通过最小欧式距离对叶片进行计算、识别。该方法克服了直角坐标系下特征提取方法计算量大,花费的时间长的缺陷。基于该方法的叶片特征提取算法的时间复杂度为[O(n)]。对于叶型有区分,且需要快速进行树叶识别的树叶数据集有很好的效果。该方法在常见的13种树木叶片中进行测试,平均正确识别率达到90%以上。     

A new approach to line and line segment clipping in homogeneous coordinates

The clipping operation is still the bottleneck of the graphics pipeline in spite of the latest developments in graphical hardware and a significant increase in performance. Algorithms for line and line segment clipping have been studied for a long time and many research papers have been published so far. This paper presents a new robust approach to line and line segment clipping using a rectangular window. A simple extension for the case of convex polygon clipping is presented as well. The presented approach does not require a division operation and uses homogeneous coordinates for input and output point representation. The proposed algorithms can take advantage of operations supported by vector–vector hardware. The main contribution of this paper is a new approach to intersection computations applied to line and line segment clipping. This approach leads to algorithms that are simpler, robust, and easy to implement.     

An algorithm for projective point matching in the presence of spurious points

Point matching is the task of finding correspondences between two sets of points such that the two sets of points are aligned with each other. Pure point matching uses only the location of the points to constrain the problem. This is a problem with broad practical applications, but it has only been well studied when the geometric transformation relating the two point sets is of a relatively low order. Here we present a heuristic local search algorithm that can find correspondences between point sets in two dimensions that are related by a projective transform. Point matching is a harder problem when spurious points appear in the sets to be matched. We present a heuristic algorithm which minimizes the effects of spurious points.     

Implementation and analysis of stream ciphers based on the elliptic curves

In this paper, implementation and analysis of three different versions of pseudorandom bit generators (PRBG) based on elliptic curves over prime and binary fields is presented. Implementations are carried out so that the algorithms could be compared in terms of time complexity and sequences could be compared in terms of periodicity, since the periodicity of all the generated streams are not available in literature. Based on the results of implementation and analysis, the pseudorandom bit generators (PRBG) most suitable for software and hardware realisations of stream cipher are identified. The software implementations of PRBG are carried out using Mathematica and the implementations in VHDL are done using the Altera Quartus IIv6.0 simulation software. The Montgomery’s point multiplication method has also been discussed and implemented for comparison with the conventional point multiplication algorithm. Together with this, faster software algorithms for field inversion and point counting are discussed.     

A Neural Network Approach to Planar-Object Recognition in 3D Space

Most existing 2D object recognition algorithms are not perspective (or projective) invariant, and hence are not suitable for many real-world applications. By contrast, one of the primary goals of this research is to develop a flat object matching system that can identify and localise an object, even when seen from different viewpoints in 3D space. In addition, we also strive to achieve good scale invariance and robustness against partial occlusion as in any practical 2D object recognition system. The proposed system uses multi-view model representations and objects are recognised by self-organised dynamic link matching. The merit of this approach is that it offers a compact framework for concurrent assessments of multiple match hypotheses by promoting competitions and/or co-operations among several local mappings of model and test image feature correspondences. Our experiments show that the system is very successful in recognising object to perspective distortion, even in rather cluttered scenes. Receiveed: 29 May 1998?,Received in revised form: 12 October 1998?Accepted: 26 October 1998     

Affine and projective active contour models

We investigate the evolution of active contours in terms of progressive modification of an initial contour following the chosen Lie group of object-to-image transformations. Because of non-fronto-parallel viewing of an object or due to relative motion between the camera and the object, the resultant image may undergo affine or projective object-to-image transformations. In a recent paper we have shown that in the case of object tracking, frame-to-frame deformations of an initial curve obtained through Euler-Lagrange descent equations of a curve functional can be used to enact a desired Lie group of plane transformations [A.-R. Mansouri, D.P. Mukherjee, S.T. Acton, Constraining active contour evolution via Lie groups of transformation, IEEE Trans. Image Process. 13 (2004) 853-863]. In this work, we propose an energy functional that encodes the Lie group transformation parameters, which in turn guide shape distortion due to oblique viewing. Additional constraints, such as transformation smoothness, are imposed on the active contour by modifying the energy functional. The functional is minimized using numerical schemes similar to the conjugate gradient technique, and the convergence properties are discussed. The success of the technique for affine and projective scenes is demonstrated with both synthetic and real image examples and compared with the related approaches.