基于曲率的全仿射曲线图像配准

为了解决视点变化造成曲线图像匹配和识别困难的问题,利用全仿射模型建立仿射变换图库,在图库样本中通过曲率信息找出与目标样本相关性最优的样本,从而达到曲线图像匹配和识别的目的。基于曲率的全仿射曲线图像匹配的方法, 首先根据全仿射模型对样本图像建立样本库,对样本库中每一个样本通过等间隔偏移进行采样,然后对采样后的子样本建立曲率样本子集,将目标图像与样本子集中的每一个样本进行快速最近邻搜索算法相似性匹配;最后通过匹配结果,找到最优匹配样本。实验结果表明,基于曲率的全仿射曲线图像配准具有较高的成功率,并且与传统算法相比具有更多的优点。     

Affine invariant classification and retrieval of texture images

In this paper, we propose a new method of extracting affine invariant texture signatures for content-based affine invariant image retrieval (CBAIR). The algorithm discussed in this paper exploits the spectral signatures of texture images. Based on spectral representation of affine transform, anisotropic scale invariant signatures of orientation spectrum distributions are extracted. Peaks distribution vector (PDV) obtained from signature distributions captures texture properties invariant to affine transform. The PDV is used to measure the similarity between textures. Extensive experimental results are included to demonstrate the performance of the method in texture classification and CBAIR.     

Silhouette-based isolated object recognition through curvaturescale space

A complete, fast and practical isolated object recognition system has been developed which is very robust with respect to scale, position and orientation changes of the objects as well as noise and local deformations of shape (due to perspective projection, segmentation errors and non-rigid material used in some objects). The system has been tested on a wide variety of three-dimensional objects with different shapes and material and surface properties. A light-box setup is used to obtain silhouette images which are segmented to obtain the physical boundaries of the objects which are classified as either convex or concave. Convex curves are recognized using their four high-scale curvature extrema points. Curvature scale space (CSS) representations are computed for concave curves. The CSS representation is a multi-scale organization of the natural, invariant features of a curve (curvature zero-crossings or extrema) and useful for very reliable recognition of the correct model since it places no constraints on the shape of objects. A three-stage, coarse-to-fine matching algorithm prunes the search space in stage one by applying the CSS aspect ratio test. The maxima of contours in CSS representations of the surviving models are used for fast CSS matching in stage two. Finally, stage three verifies the best match and resolves any ambiguities by determining the distance between the image and model curves. Transformation parameter optimization is then used to find the best fit of the input object to the correct model     

结合轮廓与形状特征的仿射形状匹配

目的 针对仿射变换下形状匹配中存在的描述子对形状的描述能力不足,以及描述子计算耗时大的问题,改进基于所有图像点投影的方法,提出一种利用轮廓计算投影面积的仿射形状匹配算法。方法 该算法分为粗匹配和精匹配两个阶段。粗匹配阶段以CSS角点作为备选特征点,首先统计轮廓投影面积分布作为特征点描述子;然后利用动态规划蚁群算法匹配两幅图片公共特征点序列,并将匹配好的特征点序列记为对应的新特征点;最后采用该新特征点划分目标曲线,得到对应的轮廓曲线;这一阶段的目的是对形状的筛选以及寻找一致的轮廓特征点,同时完成轮廓曲线的划分。精匹配阶段,采用小波仿射不变描述子,对粗匹配阶段匹配代价最小的5%的目标进行对应曲线匹配,得到精匹配阶段的匹配代价,从而实现对仿射目标的识别;精匹配弥补了描述子对轮廓细节描述不足的问题。结果 算法的平均检索速度比传统基于形状投影分布描述子提高44.3%,在MPEG-7图像库上的检索效果为98.65%,在MPEG-7仿射图像库上的查准率与查全率综合评价指标比传统的基于形状投影分布描述子高3.1%,比形状上下文高25%。结论 本文算法匹配效果好,效率高,抗噪性强,解决了仿射描述子计算速度慢、描述能力不足的问题,能有效地应用于仿射形状匹配与检索领域。     

2D affine-invariant contour matching using B-spline model

This paper presents a new affine-invariant matching algorithm based on B-Spline modeling, which solves the problem of the non-uniqueness of B-Spline in curve matching. This method first smoothes the B-Spline curve by increasing the degree of the curve. It is followed by a reduction of the curve degree using the Least Square Error (LSE) approach to construct the Curvature Scale Space (CSS) image. CSS matching is then carried out. Our method combines the advantages of B-Spline that are continuous curve representation and the robustness of CSS matching with respect to noise and affine transformation. It avoids the need for other matching algorithms that have to use the re-sampled points on the curve. Thus, the curve matching error is reduced. The proposed algorithm has been tested by matching similar shapes from a prototype database. The experimental results showed the robustness and accuracy of the proposed method in B-Spline curve matching.     

一种鲁棒的图像局部仿射不变特征提取方法

提出一种鲁棒的图像局部仿射不变特征提取方法.该方法首先对图像进行M进制小波变换,根据M进制小波变换系数的能量性质来检测图像特征点.然后以检测到的稳定特征点为中心,根据特征点周围的局部图像信息,以矩的形式构造仿射不变特征描述子.实验结果证明该方法对图像的旋转变化、尺度变化、视点变化、平移等所有仿射变换均具有较好的不变性.     

基于仿射不变约束与快速EKF滤波的航拍图像稳像

考虑到航拍机载成像平台抖动严重、视频稳像匹配环节精度不一致的特点以及航拍图像稳像技术快速、准确的要求,提出了一种结合仿射不变约束与快速扩展卡尔曼(Extend Kalman Filter,EKF)滤波的图像稳像算法。该算法首先以视频参考帧中的角点量作为特征点,通过Harris检测器选择出稳定角点;然后对待配准点构建Delaunay三角网进行初始匹配,提出利用仿射不变约束方法筛选出精确匹配点;最后利用快速EKF运动滤波方法实时估计和修正噪声的统计特性,从而解决摄像机扫描运动中存在的抖动问题。在对大量分辨率为640×480pixel的航拍图像的仿真实验中,可通过仿射不变约束实现精确的模型估计,采用的快速运动补偿方法在补偿过程中耗时为5.054ms,比传统的运动补偿方法节约了69.5%的时间。实验结果表明,该算法能够实时稳定航拍视频帧间的抖动现象,并能有效跟随场景的真实扫描。     

一种新的统计仿射不变量

本文在充分分析了现有各种仿射不变量的基础上，提出了一种新的统计仿射不变量，它对于发生尺度变化、旋转、扭曲和平移的目标具有不变性。实验结果表明，相对于传统的仿射不变量，在目标轮廓分割不完整或噪声污染的情况下，仍能够保持较高的稳健性，同时克服了基于轮廓的小波方法和傅立叶级数等方法对目标轮廓出现缺陷时的不足，
，在图像目标识别中具有实用价值。     

A theory of multiscale, curvature-based shape representation forplanar curves

A shape representation technique suitable for tasks that call for recognition of a noisy curve of arbitrary shape at an arbitrary scale or orientation is presented. The method rests on the describing a curve at varying levels of detail using features that are invariant with respect to transformations that do not change the shape of the curve. Three different ways of computing the representation are described. They result in three different representations: the curvature scale space image, the renormalized curvature scale space image, and the resampled curvature scale space image. The process of describing a curve at increasing levels of abstraction is referred to as the evolution or arc length evolution of that curve. Several evolution and arc length evolution properties of planar curves are discussed     

多尺度最稳定极限区域仿射不变特征

基于局部区域的仿射不变特征被广泛应用于目标识别、场景分类和图像检索.在已经提出的仿射不变局部特征中,最稳定极限区域特征MSER(maximally stable extremal region)在多个方面具有优越的性能.但是由于最稳定极限区域特征MSER是从单一尺度图像中提取的,当图像尺度发生较大变化时,图像的模糊会使最稳定极限区域特征的边界发生变化,从而影响特征的稳定性.针对这一问题,通过定义多尺度空间中极限区域的稳定性指标,提出一种在图像空间和尺度空间都最稳定的极限区域特征,并设计了在尺度空间进行极限区域提取的快速算法.同时,针对极限区域可以较好地描述特征轮廓的特点,将局部灰度梯度信息和形状信息相结合设计了一种新的特征描述器.这种特征被称为多尺度最稳定极限区域MMSER(multi-scale maximally stable extremal region)特征.实验结果表明,在不同仿射变化条件下,MMSER的稳定性和可识别性均优于MSER,而且其描述器的创建时间约为SIFT描述器的45%.     

基于仿射不变性的轮廓曲线局部描述符

特征点(角点、拐点、切点)只反映轮廓曲线的部分信息,为更精确地描述曲线,定义和提取一种特征点——弦高点,基于该特征点构造一种曲线局部描述符,并将其用于曲线匹配。定义的弦高点比现有的特征点更精确描述曲线的特性,能解决轮廓曲线平滑特征点少而不能被精确描述的问题。文中定义的弦高点和构造的识别向量都具有仿射不变性,且均为局部描述符,因而文中方法适合于仿射变换且在遮挡的情况下仍有效。理论分析和实验结果都证明该方法的有效性。     

Numerically Invariant Signature Curves

Corrected versions of the numerically invariant expressions for the affine and Euclidean signature of a planar curve introduced by Calabi et al. in (Int. J. Comput. Vision, 26: 107–135, 1998) are presented. The new formulas are valid for fine but otherwise arbitrary partitions of the curve. We also give numerically invariant expressions for the four differential invariants parameterizing the three dimensional version of the Euclidean signature curve, namely the curvature, the torsion and their derivatives with respect to arc length.     

基于三角网下的仿射不变几何约束的图像匹配算法研究

针对当前图像匹配方法在进行图像匹配时,主要通过度量特征向量之间的距离来完成图像匹配,导致算法鲁棒性差、误配率较高及效率较低等不足,本文提出了基于三角网下的仿射不变几何约束的图像匹配算法。首先,在尺度空间上通过Hessian矩阵对特征点进行检测,利用子块的三角特征与对角特征对SUR机制进行改进,用以生成新的特征描述子,并通过定义阀值评估策略,对图像特征点匹配,从而生成了初始匹配点;然后,引入 三角网,对初始匹配点进行聚类,以获取匹配三角形,将三角形以外的无效特征点剔除。最后,引入仿射不变几何约束,对匹配三角形进行细化,通过细化的匹配三角形获取最终的匹配特征点,有效剔除误配点,进一步提高配准精度。仿真结果表明,与当前图像匹配算法相比,本文算法具有更好的鲁棒性,且其具有更佳的匹配精度与效率,有效剔除了误配点。     

Affine invariant comparison of point-sets using convex hulls and hausdorff distances

Many object recognition or identification applications involve comparing features associated with point-sets. This paper presents an affine invariant point-set matching technique which measures the similarity between two point-sets by embedding them into an affine invariant feature space. The developed technique assumes no a priori knowledge of reference points, as is the case in many identification problems. Reference points of a point-set are obtained based on its convex hull. An enhanced version of the Modified Hausdorff Distance is also introduced and used in the feature space for comparing two point-sets. It should be noted that the technique does not attempt to obtain correspondences between the point-sets. The introduced technique is applied to two real databases and its performance is found favorable as compared to three other affine invariant matching techniques.