基于改进SURF的增强现实图像匹配方法

针对传统增强现实图像匹配算法鲁棒性不强且效率不高的问题,提出一种改进的SURF匹配算法。首先,使用SURF算法进行特征点检测,并通过Haar小波模板确定特征主方向,在得到特征主方向后构建特征描述符;由于传统SURF算法采用高达64维的矩形描述符,导致算法的计算量非常大,并且鲁棒性不强。因此,该文使用DAISY圆形描述符替代原始算法中的矩形描述符,DAISY是三层同心圆结构,每层包含8个采样点,可以得到25个维度的描述符,这种结构使得算法的鲁棒性大大增强并且降低了计算复杂度;接着,使用特征描述符计算欧氏距离进行特征点匹配;最后,对得到的匹配点集使用随机抽样一致(RANSAC)与三角不规则网络(TIN)算法进行优化,剔除误匹配点。实验结果表明,该算法虽然略微增加了时间复杂度,但鲁棒性变得更强,并且算法的效率和匹配精度也大大提高,平均精度达到了95%以上。     

基于局部近邻图的特征描述与特征匹配算法研究

特征描述和特征匹配是计算机视觉领域的重要组成部分。近年来,为了实现图像匹配上的可靠性和鲁棒性,许多特征描述算法被提出来,例如SIFT、SURF、DAISY和BRIEF等。然而,当图像发生平移、旋转、缩放等大视角变化时,这些描述符通常会失效。为了解决这个问题,在局部近邻图模型的基础上,提出一种新颖的特征描述和相似性度量方法(LNFM算法)。所提出的描述符和相似度可以很好地应用于各种流行的图像匹配算法。实验结果表明:在特征匹配过程中,该算法可以检测到可靠的匹配关系,性能较为优越。     

针对重复模式图像的成对特征点匹配

目的 含有重复模式的图像会对局部特征描述符产生歧义,因此基于局部特征的匹配算法在此类图像的匹配过程中极易产生误匹配.同时,通过研究现有的引入全局特征描述符的匹配算法,发现全局特征同样依赖于计算局部信息所得到的特征点主方向,所以此类方法在含有重复模式的图像中也不容易得到令人满意的匹配效果.为了解决这一问题,提出一种基于成对特征点的图像匹配算法.方法 该方法利用成对特征点的方向向量作为特征点对的主方向,为特征描述提供了正确的方向信息,同时引入DAISY描述符与改进后的全局上下文(globalcontext)特征描述符,提高了匹配能力.结果 分别在模拟图像与实际图像上面进行了对比匹配实验,本文算法平均的匹配正确率能达到88％以上,比其他经典的匹配算法提高了26％以上.结论 实验结果表明,本文算法克服了现有算法在特征描述与主方向分配上的缺陷,进一步提升了匹配正确率,能够有效地解决重复模式图像的匹配问题.     

基于网格运动统计的改进快速鲁棒特征图像匹配算法

针对快速鲁棒特征算法(SURF)局部不变特征描述符存在运算时间较长、匹配准确率较低的问题,文中提出基于网格运动统计的改进快速鲁棒特征图像匹配算法.首先运用Hessian矩阵行列式确定图像中的特征点,采用梯度方向改进SURF中的主方向提取方法,提高特征点主方向的准确性,并使用二进制特征描述子进行特征点描述.再对获取的特征点进行汉明距离粗匹配.最后,采用网格运动统计剔除误匹配点.在Oxford VGG标准数据集上的实验表明,文中算法在图像发生尺度、光照、旋转等变化时匹配准确率与效率较高.     

一种具有强实时性、强鲁棒性的图像匹配算法

针对描述符BRIEF对图像旋转敏感的问题,提出一种改进的描述符RIBRIEF,该描述符具有识别能力强、提取速度快、占用空间小及抗干扰能力强等优点,并具有旋转不变性.经分析,图像匹配算法的实时性较大程度上由特征点数量、匹配点搜索次数及描述符相似度计算复杂度决定,因此提出通过描述符索引与描述符聚类相结合、基于FAST稳定特征点提取和逻辑运算计算相似度等方法提高算法的整体实时性.实验结果表明,与描述符BRIEF及SURF相比较,基于描述符RIBRIEF的图像匹配算法在鲁棒性及实时性方面均具有明显优势.     

面向增强现实的SUSAN-SURF快速匹配算法

为满足增强现实对图像匹配的高实时性要求,提出了一种基于SUSAN角点检测和SURF特征描述的快速图像匹配算法。首先利用SUSAN定位特征点,然后生成特征点主方向和SURF特征描述符。其次,运用随机K-D树并结合摄像机姿态变化完成邻近点搜索,再利用基于点积的相似度度量完成初匹配。最后,通过统计特征点距离误差快速剔除误匹配点,获取最终同名点集。实验表明,该方法的单个特征点匹配耗时仅为SURF算法的23.4%,匹配正确率比SURF算法高9.7个百分点,且对光照变化、噪声干扰有较强的鲁棒性,能够满足增强现实系统对图像匹配算法的速度快、精度高和抗干扰能力强等要求。     

基于改进SURF算法的柔性装夹机器人快速工件匹配方法

针对传统SURF算法在构建局部特征描述符时耗时较长,无法满足实时性要求的问题,提出了一种改进的SURF算法。首先,运用Hession矩阵行列式（DoH）检测图像中的关键点,并利用非极大值抑制法和插值运算搜索、定位极值点;其次,采用灰度质心法确定关键点的主方向;然后,采用二进制描述符BRIEF对关键点进行描述,并利用关键点的主方向构造带有方向的特征描述符,使其具有旋转不变性;最后,运用汉明距离初步确定匹配点,再用比率检测法和RANSAC算法去除误匹配点,进而获取精准配准。实验结果表明,该改进SURF算法在应用于机器人进行柔性装夹时,对工件图像的平均匹配时间由SURF算法的214.10 ms减少到86.29 ms;而且匹配精度方面比原SURF算法提高了2.6%,因此,所提算法能够有效提高柔性装夹机器人工件图像的匹配速度和匹配精度。     

具有光照鲁棒的图像匹配方法

针对现有的基于局部特征的图像匹配算法对光照变化敏感、匹配正确率低等问题，提出一种具有光照鲁棒性的图像匹配算法。首先使用实时对比保留去色（RTCP）算法灰度化图像，然后利用对比拉伸函数模拟不同光照变换对图像的影响从而提取抗光照变换特征点，最后采用局部强度顺序模式建立特征点描述符，根据待匹配图像局部特征点描述符的欧氏距离判断是否为成对匹配点。在公开数据集上，所提算法与尺度不变特征变换（SIFT）算法、加速鲁棒特征（SURF）算法、"风"（KAZE）算法和ORB算法在匹配速度和匹配正确率上进行了对比实验。实验结果表明：随着图像亮度差异的增加，SIFT算法、SURF算法、"风"（KAZE）算法和ORB算法匹配正确率下降迅速，所提算法下降缓慢并且正确率均高于80%；所提算法特征点检测较慢和描述符维数较高，平均耗时为23.47 s，匹配速度不及另外四种算法，但匹配质量却远超过它们。对实时性要求不高的系统中，所提算法可以克服光照变化对图像匹配造成的影响。     

基于改进的SURF算子和透视变换模型的图像配准

对于传统的图像匹配算法存在特征信息少、错误匹配率高的问题,提出了一种基于改进的SURF算子和通过透视变换模型的图像配准算法。首先对传统的SURF描述符进行改进来进行特征点检测,然后用FLANN(Fast Library for Approximate Nearest Neighbors)搜索算法对检测出的角点进行粗匹配,再采用随机抽样一致(Random Samples Consensus,RANSAC)算法来消除粗匹配中误匹配的特征点对,最后将保留下来的精确匹配角点通过透视变换模型对图像进行配准。实验表明,该方法在光照、平移和模糊、旋转和尺度、视角变化具有更优的性能,提高了SURF算法的配准精度。     

一种基于关联规则的图像特征点匹配算法

针对图像间特征点匹配的SURF算法在图像遮挡、旋转和亮度改变等复杂情况下误匹配率较高的问题,本文提出了一种新的匹配算法.通过分解SURF特征点描述子向量,重新构造了匹配基准,在此基础上运用关联规则的支持度判定策略,提高了复杂情况下图像间特征点匹配的精度.计算机仿真实验表明,与SURF算法相比,本文算法的图像匹配正确率有明显提高.     

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。     

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.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance

The relative concentrations of different pigments within a leaf have significant physiological and spectral consequences. Photosynthesis, light use efficiency, mass and energy exchange, and stress response are dependent on relationships among an ensemble of pigments. This ensemble also determines the visible characteristics of a leaf, which can be measured remotely and used to quantify leaf biochemistry and structure. But current remote sensing approaches are limited in their ability to resolve individual pigments. This paper focuses on the incorporation of three pigments—chlorophyll a, chlorophyll b, and total carotenoids—into the LIBERTY leaf radiative transfer model to better understand relationships between leaf biochemical, biophysical, and spectral properties.Pinus ponderosa and Pinus jeffreyi needles were collected from three sites in the California Sierra Nevada. Hemispheric single-leaf visible reflectance and transmittance and concentrations of chlorophylls a and b and total carotenoids of fresh needles were measured. These data were input to the enhanced LIBERTY model to estimate optical and biochemical properties of pine needles. The enhanced model successfully estimated reflectance (RMSE = 0.0255, BIAS = 0.00477, RMS%E = 16.7%), had variable success estimating transmittance (RMSE = 0.0442, BIAS = 0.0294, RMS%E = 181%), and generated very good estimates of carotenoid concentrations (RMSE = 2.48 µg/cm², BIAS = 0.143 µg/cm², RMS%E = 20.4%), good estimates of chlorophyll a concentrations (RMSE = 10.7 µg/cm², BIAS = − 0.992 µg/cm², RMS%E = 21.1%), and fair estimates of chlorophyll b concentrations (RMSE = 7.49 µg/cm², BIAS = − 2.12 µg/cm², RMS%E = 43.7%). Overall root mean squared errors of reflectance, transmittance, and pigment concentration estimates were lower for the three-pigment model than for the single-pigment model. The algorithm to estimate three in vivo specific absorption coefficients is robust, although estimated values are distorted by inconsistencies in model biophysics. The capacity to invert the model from single-leaf reflectance and transmittance was added to the model so it could be coupled with vegetation canopy models to estimate canopy biochemistry from remotely sensed data.     

Mr. Twinn’s bombes

This article discusses the history and design of the special versions of the bombe key-finding machines used by Britain’s Government Code & Cypher School (GC&CS) during World War II to attack the Enigma traffic of the Abwehr (the German military intelligence service). These special bombes were based on the design of their more numerous counterparts used against the traffic of the German armed services, but differed from them in important ways that highlight the adaptability of the British bombe design, and the power and flexibility of the diagonal board. Also discussed are the changes in the Abwehr indicating system that drove the development of these machines, the ingenious ways in which they were used, and some related developments involving the bombes used by the U.S. Navy’s cryptanalytic unit (OP-20-G).