基于CPSO的二维Otsu图像分割法

二维Otsu方法同时考虑了图像的灰度信息和像素问的空间邻域信息,图像分割效果好但算法计算量较大。针对上述情况,提出一种基于混沌粒子群优化算法（CPSO）的策略,将其用于二维Otsu方法中,并与标准粒子群优化算法（SPSO）进行仿真实验对比。实验结果表明,该方法可以提高分割速度,克服SPSO的缺点,图像分割结果较理想。     

Self-consistent gradient flow for shape optimization

We present a model for image segmentation and describe a gradient-descent method for level-set based shape optimization. It is commonly known that gradient-descent methods converge slowly due to zig–zag movement. This can also be observed for our problem, especially when sharp edges are present in the image. We interpret this in our specific context to gain a better understanding of the involved difficulties. One way to overcome slow convergence is the use of second-order methods. For our situation, they require derivatives of the potentially noisy image data and are thus undesirable. Hence, we propose a new method that can be interpreted as a self-consistent gradient flow and does not need any derivatives of the image data. It works very well in practice and leads to a far more efficient optimization algorithm. A related idea can also be used to describe the mean-curvature flow of a mean-convex surface. For this, we formulate a mean-curvature Eikonal equation, which allows a numerical propagation of the mean-curvature flow of a surface without explicit time stepping.     

基于MoM评价模型的冠脉血管直径的测量

在骨架化提取出血管中心线的基础上,提出一种基于MoM评价模型的冠脉血管直径的跟踪测量方法。该算法利用血管的两条边缘线相对于中心线的对称性和最优化评价思想,通过对实际造影图像的量化测量并将其与实际直径值进行对比,发现使用提出的算法能够准确地测量血管的直径,并且可以有效地解决血管分支和重叠处直径测量问题。     

一种中文文档的非受限无词典抽词方法

本文提出了一种非受限无词典抽词模型,该模型通过自增长算法获取中文文档中的汉字结合模式,并引入支持度、置信度等概念来筛选词条。实验表明:在无需词典支持和利用语料库学习的前提下,该算法能够快速、准确地抽取中文文档中的中、高频词条。适于对词条频度敏感,而又对计算速度要求很高的中文信息处理应用,例如实时文档自动分类系统。     

用于半自动视频对象提取的自适应网格图像分割

随着MPEG－4标准的发展和基于内容的视频处理研究,视频对象平面（VOP）的有效产生成为一个关键问题。本文提出一种基于区域的自适应网格彩色图像分割方法,可用于获得半自动视频对象跟踪和提取所需的初始VOP。该方法利用CIE L＊a*b＊色彩空间的特征量,对视频序列的第一帧进行三角形网格的分裂与合并。对MPEG－4标准测试序列的分割实验取得了较好的结果。     

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

This work constitutes a theoretical study of the edge-detection method by means of the Jensen-Shannon divergence, as proposed by the authors. The overall aim is to establish formally the suitability of the procedure of edge detection in digital images, as a step prior to segmentation. In specific, an analysis is made not only of the properties of the divergence used, but also of the method's sensitivity to the spatial variation, as well as the detection-error risk associated with the operating conditions due to the randomness of the spatial configuration of the pixels. Although the paper deals with the procedure based on the Jensen-Shannon divergence, some problems are also related to other methods based on local detection with a sliding window, and part of the study is focused to noisy and textured images.     

基于模糊理论的SAR图像分割算法研究与实现

SAR图像存在强烈的相干斑噪声,传统方法不能很好对其分割。文章基于模糊理论,通过选择图像特征,构造模糊集,借助最大隶属度原则进行了SAR图像分割算法的设计,并借助SAR图像分别进行了参数调节和窗口选择的实验,获得了满意的分割结果。实验结果表明,该算法对于SAR图像分割可行有效。     

一种基于P系统的图像阈值分割方法

将P系统引入到图像阈值分割中,提出了一种基于P系统的图像阈值分割方法。采用一个两层膜的组织型P系统作为其计算框架,每个膜作为独立的并行计算单元,速度一位置模型作为进化规则,同时采用同向／反向转运规则交换和共享膜之间的对象。实验结果表明,这个基于P系统框架的阈值分割方法具有可用性和有效性,能为图像寻找最优的分割阈值。     

金属表面脏污区域的分割和量化算法研究

针对目前金属表面缺陷检测技术的研究现状,主要研究金属表面脏污检测与量化算法。结合金属表面的特点,通过对几种分割方法的比较,研究了阈值分割法中的迭代法对图像进行分割,该算法能够最大限度地保留细节信息。另外,研究了一种改进的自适应滤波算法结合像素计数法对金属表面的脏污区域进行量化处理。实验结果证明了所提出方法的有效性。     

Segmenting customers by transaction data with concept hierarchy

The segmentation of customers is crucial for an organization wishing to develop appropriate promotion strategies for different clusters. Clustering customers provides an in-depth understanding of their behavior. However, previous studies have paid little attention to the similarity of different items in transaction. Lack of categories and concept levels of items, results from item-based segmentation methods are not as good as expected. Through employing a concept hierarchy of items, this study proposes a segmentation methodology to identify similarities between customers. First, the dissimilarity between transaction sequences is defined. Second, we adopt hierarchical clustering method to segment customers by their transaction data with concept hierarchy of consumed items. After segmentation, three cluster validation indices are used for optimizing the number of clusters of customers. Through the compassion of normalized index, the segmentation method proposed by this study rendered better results than other traditional methods.