The Strong Property of Morphological Connected Alternated Filters

This paper studies connectivity aspects that arise in image operators that process connected components. The focus is on morphological image analysis (i.e., on increasing image operators) and, in particular, on a robustness property satisfied by certain morphological filters that is denominated the strong property. The behavior of alternated compositions of openings and closings is investigated under certain assumptions, particularly connectedness and a connected component preserving condition. It is shown that these conditions cannot in general guarantee the strong property of certain connected alternated filters because of issues related to the locality of the filters. As treated in the paper, there have been a series of misunderstandings in the literature concerning this topic, and it is important to clarify them. The root cause of those problems is discussed, and a solution is indicated. The class of connected openings and closings used to build connected alternated filters should therefore be defined to avoid such situations, since the strong property of alternated filters should be a distinctive characteristic of this class.

Classification of Fuzzy Mathematical Morphologies Based on Concepts of Inclusion Measure and Duality

Mathematical morphology was originally conceived as a set theoretic approach for the processing of binary images. Extensions of classical binary morphology to gray-scale morphology include approaches based on fuzzy set theory. This paper discusses and compares several well-known and new approaches towards gray-scale and fuzzy mathematical morphology. We show in particular that a certain approach to fuzzy mathematical morphology ultimately depends on the choice of a fuzzy inclusion measure and on a notion of duality. This fact gives rise to a clearly defined scheme for classifying fuzzy mathematical morphologies. The umbra and the level set approach, an extension of the threshold approach to gray-scale mathematical morphology, can also be embedded in this scheme since they can be identified with certain fuzzy approaches.

基于单亲遗传算法和导向算子的图像分形编码

基于图像的近距自相似性,用一种采用实数编码的单亲遗传算法完成图像分形压缩中的最优码本匹配,针对含有边缘的Range块的匹配,通过一个导向算子使边缘R块的最优匹配搜索沿着图像的边缘进行。实验结果表明,相对于基本分形压缩算法,在基本保证解码图像主观质量的前提下,该方法的速度提高了约60倍。     

基于蚁群算法的XML概率查询策略与算法优化

针对XML数据半结构化的特点及概率查询理论,结合蚁群算法,提出添加杂交算子和更新信息素的方法,该方法不仅能动态选择数据查询方向,而且能避免无效查询,扩大数据查询范围,提高收缩效率。模拟测试证明了该方法能优化XML查询。     

平均曲率运动的三种实现方案的比较研究

讨论了曲率运动演化方程的三种数值方案:离散中值滤波方案、显式水平集方案和半隐式水平集方案的原理与算法,并对它们的效率、精度以及旋转不变性等性能进行了对比实验研究.结果表明,半隐式加性算子分裂(AOS)算法相对于另两种方案性能上明显占优.     

支持向量机序贯最小优化算法推导的改进

已有文献中的支持向量机SMO算法推导过程计算复杂,该文给出一个简洁推导。整个推导过程没有复杂的计算,除了误差函数外,不需引入其它中间变量。     

嵌入式GPS／GIS系统设计的几个关键问题及解决方法

提出嵌入式GPS/GIS系统设计中的几个关键技术问题并给出解决方案。对GPS数据质量采用神经元辨识的方法进行控制;对大数据量底图数据采用一种新的地图综合方法建立多级显示机制,节省内存,提高图形显示效率;建立基于la-bel的空间算子实现方式,完成采集图斑的现场变更,减少内业数据处理的工作量。实际应用表明,这些方法能够满足嵌入式GPS/GIS系统应用于土地调查业务的需要,提高了调查效率。     

一种改进的基音周期提取算法研究

现有的基音周期提取方法在准确度和稳健性上存在一定的局限性,很难准确地提取出信噪比较低的语音信号的周期.针对这一问题,提出一种基于小波变换的基音周期提取改进算法,将TEO(Teager Energy Operator)算子与二进小波变换结合起来,首先进行清浊判定,然后只对浊音帧采取多尺度小波分析提取周期,提出用幅度信息和出现概率信息校正二进小波模极大值间距,从而得到准确的周期.计算机仿真结果表明,与传统方法相比,不仅提高了处理效率,而且具有更高的精确度和稳定性.     

模糊控制器输出值不变的两个充分条件

模糊控制器通常由模糊化、模糊推理以及清晰化三部分构成, 而模糊推理决定了一个由输入论域到输出论域的模糊映射. 当模糊映射为常值映射时, 任意选择模糊化和去模糊化方式, 模糊控制器的输出值不因输入信号变化而改变. 本文给出了模糊映射为常值映射的两个充分条件, 并将结论从单入单出模糊系统推广到多入单出模糊系统.     

基于谱分解的中立型时滞系统观测器

针对线性中立型时滞系统, 利用线性算子半群的谱分解理论进行观测器设计. 在中立型项的范数小于一的条件下, 利用谱理论并结合投影算子, 将无穷维系统解的相空间分解为有限维不稳定广义特征子空间和无限维稳定广义特征子空间的直和. 进而利用线性算子半群的无穷小生成元得到具有积分微分形式的观测器方程, 并证明了观测器误差方程的渐近稳定性. 数值实验证实了所提设计方法的有效性.