基于形状保持主动轮廓模型长直条的检测

通过形状约束方程（组）与一般主动轮廓模型结合,将目标形状与主动轮廓模型融合到统一能量泛函模型中,提出一种形状保持主动轮廓模型。模型通过参数化水平集函数的零水平集表示某一类特定形状,不仅达到了分割即目标的目的,而且能够给出特定目标的定量描述。根据形状保持主动轮廓模型,建立一个用于长直条状目标检测的统一能量泛函模型,导出相应的Euler-Lagrange 常微分方程并用水平集方法实现了长直条状区域的检测。此形状保持模型的一种特殊情况可以用于直线状地平（海天）线提取。实验结果表明,该模型不仅能够准确地检测出给定图像中的长直条状区域而且有很强的抗噪、抗变形及遮挡性能     

基于主动轮廓的声呐图像水雷识别方法

针对声呐图像具有噪声大、目标边缘模糊等特点,提出了一种基于主动轮廓的声呐图像水雷目标识别方法.首先根据水雷目标在声呐图像中的形状特征,采用水平集思想,得到了引入超椭圆形状约束的水平集函数;然后根据水雷目标在声呐图像中的灰度特征,采用Chan-Vese模型的演化思想,提出了一种基于超椭圆形状约束的多相水平集主动轮廓模型.将该模型用于声呐图像水雷目标的识别实验,实验结果表明,该方法对声呐图像中的水雷目标具有很好的识别效果,而且具有抗噪性和抗变形性能.     

基于形状保持的CV变分水平集矩形目标分割EI北大核心CSCD

目标在被局部遮挡、与背景灰度信息相似以及纹理比较明显等情况下,传统CV模型无法进行准确分割.为此,将模型中活动轮廓曲线的水平集函数用先验形状的水平集函数来代替,使得曲线在演化过程中始终保持某一类特定形状,从而实现了目标分割过程中的形状保持.根据形状保持的CV变分水平集分割模型建立适用于矩形目标分割的能量函数模型,推导出一组Euler-Lagrange常微分方程;通过水平集函数的不断迭代演化最终实现了矩形目标的分割;最后演化得到的水平集函数是对矩形目标的定量描述.3组实验结果证明,该模型能够解决复杂情况下的矩形目标分割问题,且具有计算量小、鲁棒性强的优点.     

基于形状保持的CV变分水平集矩形目标分割

目标在被局部遮挡、与背景灰度信息相似以及纹理比较明显等情况下,传统CV模型无法进行准确分割.为此,将模型中活动轮廓曲线的水平集函数用先验形状的水平集函数来代替,使得曲线在演化过程中始终保持某一类特定形状,从而实现了目标分割过程中的形状保持.根据形状保持的CV变分水平集分割模型建立适用于矩形目标分割的能量函数模型,推导出一组Euler-Lagrange常微分方程;通过水平集函数的不断迭代演化最终实现了矩形目标的分割;最后演化得到的水平集函数是对矩形目标的定量描述.3组实验结果证明,该模型能够解决复杂情况下的矩形目标分割问题,且具有计算量小、鲁棒性强的优点.     

基于区域混合活动轮廓模型的医学图像分割

针对变分水平集算法在图像分割过程中计算量较大且收敛速度慢的现象, 在一些基于区域的活动轮廓模型基础上提出了一种新的基于区域混合模型的非凸正则化活动轮廓模型。该模型构造了一个新的能量泛函,该能量泛函结合了考虑图像局部聚类性质的LBF模型和测地线模型,增加了非凸正则化项,加快了轮廓曲线的收敛速度,可以很好地保持区域形状并能防止边缘过平滑,然后通过经典有限差分法求得能量泛函的极小值。最后,在合成图像和医学图像上做了仿真实验,结果表明,该算法具有较快的收敛速度 和很好的鲁棒性,分割结果也较准确。     

基于形状约束的LBF模型的水平集分割

由于LBF模型是通过高斯核函数来拟合局部内外的区域信息,是典型的局部区域模型。此外医学图像的复杂性且分割经常出现类似特定形状的目标。为了更快地找到局部的区域特征形状(如圆或椭圆),提出将初始水平集与椭圆方程的差异作为形状能量项融入到LBF模型中,在演化过程中无需经过仿射变换来更新相应的形状,只需对初始轮廓和形状水平集差异能量函数进行迭代计算。在实验结果中,选取4幅眼睛图片分别对LBF模型和加入形状项的LBF模型进行比较分析。结果表明,所提出的模型能够准确地检测图像中椭圆状的目标,且分割准确率达到了96%,也解决了图像灰度不均匀、对噪声敏感的问题。     

基于优化活动轮廓模型的SAR影像海陆分割方法研究*

SAR（合成孔径雷达）影像具有很强的乘性斑噪,给图像分割带来了困难。本文利用Gamma分布拟合SAR影像,并将其用于构造基于区域信息的能量泛函,提出了一种基于活动轮廓模型的SAR影像海陆自动分割方法。该方法在能量泛函中同时融合了边缘信息和区域信息,既有利于边界精确定位又有利于降低乘性斑噪的影响,利用活动轮廓演化模型,通过变分水平集方法推动活动轮廓曲线向海岸线演化,在最小化特定的能量泛函的约束下,使活动轮廓与海岸线重合,达到影像分割的目的。同时针对该模型提出了优化方法提高其计算效率,使本文提出的分割算法更加实用。     

基于变异系数和模糊集的活动轮廓图像分割模型

由于图像分割具有模糊性,提出了一个对灰度不均匀、高噪声图像的分割模型。该模型以模糊能量泛函为基础,结合区域和边缘信息,利用变异系数作为局部区域统计量,避免了噪声对分割的干扰,很好地提取了图像信息。区域能量可以平衡目标和背景的重要性,驱使初始轮廓向目标边界移动。边缘能量对伪水平集函数进行正则化,保持曲线演化过程中的平滑性。在求能量泛函极小值时,直接计算新旧能量泛函的差值以更新伪水平集。对于高噪声以及混合噪声和强度不均匀的合成和真实图像的分割结果表明,本文模型具有较好的分割效果。     

基于区域能量最小和主动轮廓模型的医学目标提取

针对传统主动轮廓模型在目标强边缘处容易产生振荡和弱边缘处容易泄露的缺点,提出了一种基于区域能量最小和主动轮廓模型的医学目标提取模型。这一基于目标灰度统计概率和水平集的主动轮廓分割模型,把能量函数表示为在目标区域内对像素点属于目标概率的积分,并在水平集框架下对能量函数最小化,得到分割的迭代方程;同时,通过附加的速度约束项,使得主动轮廓在越过目标边缘时降低速度,大大提高了分割的收敛性和准确度。通过大量冠状动脉和二尖瓣的分割实验以及与几种传统主动轮廓模型和手工提取的比较,表明该模型在医学图像分割方面的健壮性、准确性和有效性。     

基于先验形状的混杂活动轮廓模型及其在图像分割中的应用

提出了一种新颖的基于先验形状学习的混杂活动轮廓(SHAC)模型,该模型采用变分水平集方法,融合自适应区域信息与边界信息,运用主成分分析的方法从给定的含有目标物体轮廓的训练集学习得到最佳形状信息,并将其作为先验形状。将自适应区域特征和轮廓特征作为局部信息,先验形状作为全局信息,在迭代过程中结合全局和局部信息实现对演化曲线的形变进行指导和约束,达到分割目标物体的目的。通过定量和定性地分析低对比度的乳腺核磁共振图像中的乳腺轮廓的分割,以及具有复杂背景的自然图像中感兴趣区域的分割结果,验证了SHAC模型比传统活动轮廓模型具有更高的准确率,表明了该模型不仅提高了图像分割中对弱边界的识别度,减弱了非目标轮廓的干扰,而且具有良好的抗噪能力。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。