数字图像边缘检测算子的性能实验比较

本文对数字图像中几种具有代表性的边缘检测算子进行了理论分析，并通过VC编程实验，对各种算法进行实现，通过比较得出了各自的优缺点和适用范围。     

Background-subtraction using contour-based fusion of thermal and visible imagery

We present a new background-subtraction technique fusing contours from thermal and visible imagery for persistent object detection in urban settings. Statistical background-subtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regions-of-interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then fused into a single image. An A^* path-constrained search along watershed boundaries of the regions-of-interest is used to complete and close any broken segments in the fused contour image. Lastly, the contour image is flood-filled to produce silhouettes. Results of our approach are evaluated quantitatively and compared with other low- and high-level fusion techniques using manually segmented data.     

A fast digital Radon transform—An efficient means for evaluating the Hough transform

A fast digital Radon transform based on recursively defined digital straight lines is described, which has the sequential complexity of N² log N additions for an N × N image. This transform can be used to evaluate the Hough transform to detect straight lines in a digital image. Whilst a parallel implementation of the Hough transform algorithm is difficult because of global memory access requirements, the fast digital Radon transform is vectorizable and therefore well suited for parallel computation. The structure of the fast algorithm is shown to be quite similar to the FFT algorithm for decimation in frequency. It is demonstrated that even for sequential computation the fast Radon transform is an attractive alternative to the classical Hough transform algorithm.     

NaI多道脉冲幅度分析系统在燃料元件破损监测中的应用研究

介绍了船用堆燃料元件破损监测中较常用的两种方法.通过分析其缺陷,提出了用NaI多道脉冲幅度分析系统测量特征核素(131I、137Cs)的方法,有效避免了监测中的干扰因素的影响,降低了定量监测中的误报率,提高了燃料元件破损监测的效率和置信度.     

基于异常检测的NVP表决器

一般的表决器多是针对一维输出进行表决,构建表决器相对应的决策树,预先给出阈值来制定表决策略。但是对于多维输出的表决器研究相对较少,尤其是输出各个变量之间非独立的情况下,不能将多维输出的每个变量进行单独表决,否则会引入异常点,影响表决结果。实验表明,将异常检测技术引入到表决器中,净化需要表决的数据,可以提高表决结果的准确率。     

入侵检测在存储区域网中的应用

从SAN(存储区域网)的安全隐患出发,分析了SAN在应用环境中受到的三种典型威胁。结合现行的入侵检测技术给出一个可行的解决方案。     

工业计量点无线监测系统

工业企业是我国能源消耗大户。为了加强工业企业的能源计量管理,保障工业企业节能降耗的基础工作,文章在分析了现有工业计量体系所存在的技术难点的基础上,提出将无线传感器网络技术应用于能源计量管理的实现方法,同时介绍了工业计量点无线监测系统的构成和优点。     

复杂场景实时目标检测方法

针对含有非平稳背景的复杂场景,提出一种基于空间混合高斯模型的实时目标检测方法.该方法以混合高斯模型作为颜色分布的统计框架,并在空间邻域中利用背景与前景隶属度之间的竞争确定像素的归属,提高了检测准确率;同时通过基于偏差均值的匹配判断和低权重模型的移除提升了混合高斯统计框架的性能,以实时地对运动目标进行准确的检测.实验结果表明,文中方法对非平稳背景有很好的适应能力,在检测准确率和运行效率上均优于其他检测方法.