基于核特征距离的局部活动轮廓模型

提出了一种基于核特征距离局部活动轮廓分割模型。在模型中使用核特征距离来构造局部拟合能量,从而可以获取精确的局部图像特征,可以分割存在灰度不均匀的图像。并通过引入水平集规范项以避免水平集演化的重新初始化,提高了分割的效率。实验结果表明,本模型可以很好地克服灰度不均匀性,同时在分割精度上有了较大的提升,特别是分割速度比LBF模型快1.3～1.5倍。     

基于超像素/像素协同约束和稀疏分解的活动轮廓模型

针对水平集图像分割模型的分割结果不够准确且对初始轮廓位置和噪声敏感问题,提出了超像素/像素协同约束和稀疏分解的活动轮廓模型。首先引入超像素提取图像块信息构造符号压力函数防止轮廓在演化过程中陷入局部最优;其次,构建了基于超像素/像素协同约束的能量泛函以弥补超像素无法保留局部细节的缺陷;同时,为了解决基于非全局信息的活动轮廓模型演化速度慢的问题,提出模型利用超像素块加速轮廓演化;最后引入了稀疏分解对模型进行优化以减弱局部噪声对分割精度的影响。与多种水平集分割模型的实验结果对比,证明了提出方法的有效性,尤其与原始的二值选择和高斯滤波正则化水平集模型相比,提出方法对噪声和初始轮廓位置不敏感,平均Jaccard相似度系数提升了34%。     

基于改进活动轮廓模型和视觉特性的图像分割方法

提出一种基于改进活动轮廓模型和视觉显著性分析的图像分割方法。与传统的水平集模型不同,改进的活动轮廓模型不需要进行初始化和计算符号距离函数,从而有效地提高曲线演化效率。在此基础上,提出了基于标记的多相水平集分割方法,有效地解决了复杂图像存在的灰度不均性问题。另外,为避免初始轮廓位置对分割结果的影响,采用视觉显著图获取水平集初始轮廓位置,通过对该显著图进行OSTU分割提取初始轮廓。通过实验分析,提出的方法在分割结果、速度和复杂度上较之传统的CV模型都有明显的改进。     

结合全局和双核局部拟合的活动轮廓分割模型

针对可缩放区域拟合（RSF）模型对初始轮廓敏感的缺点,提出了一种结合全局和局部图像信息的变分水平集活动轮廓模型。该模型设计了一个灰度域上的核函数,将其与RSF模型空域核的线性组合作为局部能量项,弥补了采样权值仅与空间距离有关的缺陷,提高了分割精度;构造了带有自适应全局指示函数的面积项,作为全局拟合力,提高了模型的收敛速度且避免陷入局部极小值;使用了高斯滤波方法,规则水平集函数,使其保持光滑,并避免了复杂的重新初始化过程。实验结果表明,该模型初始化灵活,对灰度不均匀图像有很好的分割效果     

边缘与区域联合活动轮廓模型研究

图像分割在计算机视觉和模式识别中起着重要的作用,近年来基于活动轮廓和水平集方法的图像分割模型得到了广泛的研究。提出一种新的边缘与区域相结合的活动轮廓模型,并利用水平集方法来进行曲线的演化。通过合成图像和真实图像的实验,提出的模型与经典的Chan-Vese模型相比,不但提高了抗噪能力,而且可以更准确地检测图像的边缘,同时分割精度也得到了较大的提高。     

结合FCM和RSF模型的医学图像分割方法

针对现有活动轮廓模型初始化敏感的缺点,提出一种新的基于区域的活动轮廓模型。该模型采用模糊c均值聚类(FCM)算法对图像进行预分割,将预分割结果二值化为种子标记矩阵,作为下一步水平集演化的初始轮廓,解决了初始化敏感问题;引用RSF(Region-Scalable Fitting)模型的局部区域项作为能量项,提高了分割灰度分布不均匀图像能力;使用高斯滤波方法正则化水平集函数,避免了重新初始化过程,提高了分割效率。实验结果表明:该模型避免了初始化,具有分割结果精确、分割效率高的特点。     

基于改进DRLSE水平集模型的图像分割

针对 DRLSE 水平集模型对噪声敏感、依赖初始轮廓位置以及演化速度缓慢等不 足,利用小波变换和小波阈值去噪的方法,构造对噪声不敏感的边缘信息刻画矩阵,定义基于 图像信息的边缘停止函数和自适应权重系数,获得了改进的 DRLSE 水平集图像分割模型。利 用有限差分法对模型求解,并采用 Jaccard 相似度作为评价模型的定量分析方法,数值结果显示 改进的模型及算法对图像分割的有效性,克服了 DRLSE 水平集模型分割含噪图像以及定义初 始轮廓位置的局限性,提高了 DRLSE 水平集模型的计算效率和图像分割精度。     

梯度向量场通量能量驱动的主动轮廓模型

提出了一种基于梯度向量场通量能量的水平集图像分割算法.通过加入约束符号距离函数的能量项,并极小化该能量函数得到的变分表达式主要具有4条优于传统主动轮廓模型的优点.一是可以克服分割弱边界目标的困难;二是水平集函数不但可以灵活初始化,而且可避免在演化过程中重新初始化为符号距离甬数;三是水平集函数数值化可采用简单的有限差分方法,计算效率得到了极大的提高;四是仅用一个初始轮廓就可以自动检测带孑L目标的内轮廓.对合成和真实图像的分割结果表明:对弱边界目标和灰度分布不均目标的分割效果分别优于测地线模型(GAC)和C-V主动轮廓模型.     

基于水平集的医学图像快速分割方法

针对高噪声、低对比度的医学图像难以快速准确分割的问题,结合基于像素的传统方法和基于水平集的活动轮廓模型,提出了一种混合的医学图像分割新技术.首先依据待分割对象的先验知识交互选取感兴趣区域.然后由传统的方法和基于水平集的C-V模型结合实现感兴趣区域图像的预分割.预分割的结果直接作为窄带变分水平集模型的初始轮廓,演化曲线在很短的时间内准确收敛到待分割物体的边缘.     

一种新的基于自适应分数阶的活动轮廓模型

区域可调拟合(region scalable fitting, RSF)活动轮廓模型在分割弱纹理、弱边缘图像时,优化易陷入局部极小导致曲线演化速度缓慢;同时该模型中的局部拟合项为高斯核函数,导致目标的边界模糊,影响分割精度.针对该问题,提出了一种基于自适应分数阶的活动轮廓模型,用于图像的分割.首先将全局G-L(Grünwald-Letnikov)分数阶梯度融合到RSF模型中,以增强灰度不均匀和弱纹理区域的梯度信息,从而提高对曲线初始位置选择的鲁棒性,并提高了图像分割的精度和速度;然后用双边滤波函数替换局部拟合项中的高斯核函数,解决了高斯核函数在演化过程中造成的边界模糊问题;最后根据图像的梯度模值和信息熵构建自适应分数阶阶次的数学模型,并计算出最佳分数阶阶次.理论分析和实验结果均表明:提出的算法可以用于灰度不均匀和弱纹理、弱边缘区域的图像分割,并能根据图像的特征自适应计算最佳分数阶阶次,避免曲线演化陷入局部最优.用多幅图像进行实验,得出该方法的分割精度和分割效率都有较大提高.     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.