一种保形的快速图象形态细化算法

骨架是一种重要的图象目标几何特征,对不同形状的图象目标,如何快速地获得其非畸变骨架,是进行图象目标的形状分析、特征提取、模式识别等应用的前提。基于数字形态学的形态细化是获取图象目标骨架的有效细化方法之一。它采用具有一定形状的预定义结构元素,对图象进行形态薄化运算,仅需进行移位和逻辑运算就能完成。但是形态细化一般使用序贯细化算法,在每次细化迭代过程中,只能采用单一的结构元素对目标进行薄化,因此存在关     

一种基于图象特征的形态采样及插值方法

本文提出了一种以形态滤波图象为内容的、基于图象形态特征的图象采样及与之配套的图象插值方法.该方法以保持图象的某种形态特征为目的,通过不同结构的形态采样及形态插值元素(结构元素)以及反映图象形状、纹理或轮廓特征的形态滤波图象作为参考图象,对于图象实行依据其内容的采样及插值重构.以形态梯度图象作为参考图象的实验结果表明,形态采样及插值方法在保持图象形态及几何特征方面确有优于传统方法之处,若将形态采样方法与形态插值方法结合使用,插值重构图象在保持图象轮廓特征方面表现出明显的优势.     

用于二维形状描述圆周分解法

本文提出一种新的二维形状描述方法，用于描述二值和灰度图像物体的形状信息。该方法使用同心环状区域对二维形状进行分解，产生一组描述强度值的投影函数，并通过傅立叶变换实现旋转不变性和抗干扰能力。该方法与物体是否具有单一边界无关，能够适应各种复杂的、边界不规则的或者不连通的物体形状。此外，该方法还能够直接应用于灰度图象。     

利用形状与空间位置特征检索二值商标图象

为了充分利用商标图象的内部信息，以提高商标图象的检索精度，提出了一种综合利用商标形状特征与共内部空间位置关系持征来检索二值商标图象的方法，由于二值商标属于人工图象，大多数二值商标都是由一些边界分明的几何形状体构成，因此可把二值商标图象看作是由一些具有显著形状特征的区域构成的集合体，对这些集合体首先利用矩特征进行形状的相似性度量，然后利用投影分类的方法匹配空间位置关系，该方法基于这一思想，既考虑了商标涔部各组成部分的形状特征，又兼顾了它们之间的空间位置关系，将整个检索过程分为初级检索与检索求精两个阶段，由于该方法保证了整体与局部的一致性，因此具有很好的检索精度，与仅仅利用图象的形状特征进行检索的实验结果相比，其检索结果更加符合人的视觉感受。     

一种基于自适应形态学结构元素的车牌定位算法

针对传统的基于数学形态学的车牌定位算法结构元素选取的弊端,即依据经验或实验而选择一个固定大小和形状的结构元素对车牌图像进行全局处理,导致定位算法的普适性和鲁棒性低,提出了一种基于自适应结构元素的车牌定位算法,算法充分利用车牌二值图像自身信息,通过计算字符水平边缘所形成的线段长度的均值作为结构元素,因此结构元素的大小能随着车牌图像的不同而自适应调整,更加有效地定位车牌目标区域。实验结果证明,算法具有较强的自适应能力,定位准确率满足应用需要。     

基于图象集合运算的矿图扫描图象二值化方法

在分析了多种类型的图象二值化方法在矿图扫描图象分割中存在的问题后，依据图象的集合运算原理，提出了一种兼顾图象整体灰度水平及象元邻域特征的二值化方法——多阈值动态自适应二值化方法。该方法可克服矿图扫描图象二值化过程中出现的线划粘连或断线现象，且方法简单、容易实现。     

基于小波域的自适应图象盲水印算法

文章提出了一种多尺度小波域的自适应盲水印算法,水印采用有意义二值图。将0/1水印值嵌入到图象三级小波分解后的细节子带系数中,嵌入方向由高分解层向低分解层进行。嵌入过程根据选定位置点的3个细节子带系数的间隔差异,采取不同的嵌入策略。水印提取不需原图,属于盲水印提取,提取水印亦是二值图,效果直观。经攻击实验证明,对图象噪声、剪切和压缩具有一定的鲁棒性,是一种可行的水印算法。     

二值图象广义边界编码压缩方法

本文提出一种与游程相关的二值图象广义边界概念和及对编码方法，并给出实现算法的恢复方法，最后通过对几幅二值图象压缩结果与游程编码，二维自适应跳白块编码方法进行比较和分析，表明本文提出了的广义边界编码压缩方法的压缩性能比另两种压缩方法优越，是一种易于实现的高效率的二值图象压缩方法。     

文档图象的版面分析一基于数学形态学的方法

提出了基于Hough变换的结构元素构造方法(HTSEC)以及基于数学形态学的分割方法(MMS)，即首先将灰度文档图象利用半色调技术转换为二值图象，利用Hough变换动态构造结构元素，然后利用数学形态学方法对版面进行划分并将其分为文字区、图形区和图象区．     

矩形形态滤波器

矩形形态是一种最基本的灰度形态,在图像分析中有着重要的应用．为有效地检测出图像中的矩形形态,提出了一种矩形形态滤波器．首先定义了矩形形态滤波器的结构元素,然后定义了两种滤波模式：序位滤波和序位均值滤波．实验结果表明,矩形形态滤波器可以有效地从二值图像、二值噪声图像和灰度图像中检测出指定大小和方向的矩形形状．     

Comparison between the morphological skeleton and morphologicalshape decomposition

The morphological skeleton and morphological shape decomposition (MSD) are two popular approaches for morphological shape representation. Each method represents an object as an algebraic combination of a number of components, where each component is given by a locus of points dilated by a specified structuring-element homothetic. This correspondence develops a theoretical comparison between the two methods. Combining the theoretical results with several representation cost measures, we make a concrete comparison of the efficiency of the two methods. The results indicate that for complex objects-i.e., objects requiring a full range of homothetic sizes in the morphological skeleton representation-the MSD represents objects more efficiently than the morphological skeleton for three of four suggested cost measures     

基于骨架层次分解的目标的图表示

基于骨架的目标表示技术是模式识别和计算机视觉的重要研究内容,近年来人们提出了许多骨架化算法,但是有关利用骨架信息表示并识别目标的研究还非常有限。Ablameyko等1996年提出了通过分解由距离标号的骨架为有意义的结构基元从而获得目标的层次结构图的方法。该图可以准确地刻画基元之间的拓扑关系,但是它对于骨架中的噪声比较敏感。主要表现为噪声基元破坏其它基元的完整性和图的稳定性。该文采用将分支编组为分支链以及构造多尺度结构图的改进策略来克服这些缺点,最终获得了目标的节点数更小、节点显著度更高、节点间连接关系更稳定的多尺度图,从而显著地提高后续利用不精确图匹配技术进行目标识别的效率。这项技术已经被应用于一个基于形状特征的图像数据库检索系统中。     

Efficient morphological shape representation by varying overlapping levels among representative disks

The morphological skeleton transform, the morphological shape decomposition, and the overlapped morphological shape decomposition are three basic morphological shape representation schemes. In this paper, we propose a new way of generalizing these basic representation algorithms to improve representational efficiency. In all three basic algorithms, a fixed overlapping policy is used to control the overlapping relationships among representative disks of different sizes. In our new algorithm, different overlapping policies are used to generate shape components that have different overlapping relationships among themselves. The overlapping policy is selected dynamically according to local shape features. Experiments show that compared to the three basic algorithms, our algorithm produces more efficient representations with lower numbers of representative points.     

利用自适应形态学实现遥感水体图像增强

遥感水体图像内容信息复杂，为了滤除水体外噪声干扰方便后续水体区域分析，在保持水体区域边缘的同时增强对比度较低的遥感水体图像。提出了一种利用自适应椭圆结构元素的形态学遥感水体图像对数增强方法。利用线性结构张量估计图像特征值和特征向量，利用该特征建立自适应椭圆结构元素，更好地保持水体边缘；定义自适应形态学膨胀腐蚀，组合衍生出自适应形态学开闭运算；利用自适应形态学运算构造对数增强运算，达到滤除非目标区域噪声并增强遥感水体图像的目的。实验结果表明，相比传统和自适应形态学增强方法，该方法不仅能够滤除目标外噪声干扰，增强水体区域目标，而且保证水体边缘位置和形状，提高了对比度和信息熵。     

Many-objective evolutionary algorithm based on adaptive weighted decomposition

Decomposition is a representative method for handling many-objective optimization problems with evolutionary algorithms. Classical decomposition scheme relies on a set of uniformly distributed reference vectors to divide the objective space into multiple subregions. This scheme often works poorly when the problem has an irregular Pareto front due to the inconsistency between the distribution of reference vectors and the shape of Pareto fronts. We propose in this paper an adaptive weighted decomposition based many-objective evolutionary algorithm to tackle complicated many-objective problems whose Pareto fronts may or may not be regular. Unlike traditional decomposition based algorithms that use a pre-defined set of reference vectors, the reference vectors in the proposed algorithm are produced from the population during the search. The experiments show that the performance of the proposed algorithm is competitive with other state-of-the-art algorithms and is less-sensitive to the irregularity of the Pareto fronts.     

具有旋转不变性的图象骨架变换

本文在详细研究数字形态学求取目标图象骨架的基础上，根据形态学距离的定义提出了一种特殊的结构元素设计方法，使得形态学骨架变换具有旋转不变性，同时提高了计算效率，使之适用于实际的模式识别和计算机视觉匹配。     

Skeletonization of Ribbon-like shapes based on a new wavelet function

A wavelet-based scheme to extract skeleton of Ribbon-like shape is proposed in this paper, where a novel wavelet function plays a key role in this scheme, which possesses three significant characteristics, namely, 1) the position of the local maximum moduli of the wavelet transform with respect to the Ribbon-like shape is independent of the gray-levels of the image. 2) When the appropriate scale of the wavelet transform is selected, the local maximum moduli of the wavelet transform of the Ribbon-like shape produce two new parallel contours, which are located symmetrically at two sides of the original one and have the same topological and geometric properties as that of the original shape. 3) The distance between these two parallel contours equals to the scale of the wavelet transform, which is independent of the width of the shape. This new scheme consists of two phases: 1) Generation of wavelet skeleton-based on the desirable properties of the new wavelet function, symmetry analyses of the maximum moduli of the wavelet transform is described. Midpoints of all pairs of contour elements can be connected to generate a skeleton of the shape, which is defined as wavelet skeleton. 2) Modification of the wavelet skeleton. Thereafter, a set of techniques are utilized for modifying the artifacts of the primary wavelet skeleton. The corresponding algorithm is also developed in this paper. Experimental results show that the proposed scheme is capable of extracting exactly the skeleton of the Ribbon-like shape with different width as well as different gray-levels. The skeleton representation is robust against noise and affine transformation.     

A new shape decomposition scheme for graph-based representation

Nowadays, the part-based representation of a given shape plays a significant role in shape-related applications, such as those involving content-based retrieval, object recognition, and so on. In this paper, to represent both 2-D and 3-D shapes as a relational structure, i.e. a graph, a new shape decomposition scheme, which recursively performs constrained morphological decomposition (CMD), is proposed. The CMD method adopts the use of the opening operation with the ball-shaped structuring element, and weighted convexity to select the optimal decomposition. For the sake of providing a compact representation, the merging criterion is applied using the weighted convexity difference. Therefore, the proposed scheme uses the split-and-merge approach. Finally, we present experimental results for various, modified 2-D shapes, as well as 3-D shapes represented by triangular meshes. Based on the experimental results, it is believed that the decomposition of a given shape coincides with that based on human insight for both 2-D and 3-D shapes, and also provides robustness to scaling, rotation, noise, shape deformation, and occlusion.