A new graph cut-based multiple active contour algorithm without initial contours and seed points

This paper presents a new graph cut-based multiple active contour algorithm to detect optimal boundaries and regions in images without initial contours and seed points. The task of multiple active contours is framed as a partitioning problem by assuming that image data are generated from a finite mixture model with unknown number of components. Then, the partitioning problem is solved within a divisive graph cut framework where multi-way minimum cuts for multiple contours are efficiently computed in a top-down way through a swap move of binary labels. A split move is integrated into the swap move within that framework to estimate the model parameters associated with regions without the use of initial contours and seed points. The number of regions is also estimated as a part of the algorithm. Experimental results of boundary and region detection of natural images are presented and analyzed with precision and recall measures to demonstrate the effectiveness of the proposed algorithm.     

An efficient bit-based feature selection method

Feature selection is about finding useful (relevant) features to describe an application domain. Selecting relevant and enough features to effectively represent and index the given dataset is an important task to solve the classification and clustering problems intelligently. This task is, however, quite difficult to carry out since it usually needs a very time-consuming search to get the features desired. This paper proposes a bit-based feature selection method to find the smallest feature set to represent the indexes of a given dataset. The proposed approach originates from the bitmap indexing and rough set techniques. It consists of two-phases. In the first phase, the given dataset is transformed into a bitmap indexing matrix with some additional data information. In the second phase, a set of relevant and enough features are selected and used to represent the classification indexes of the given dataset. After the relevant and enough features are selected, they can be judged by the domain expertise and the final feature set of the given dataset is thus proposed. Finally, the experimental results on different data sets also show the efficiency and accuracy of the proposed approach.     

使用非均匀量化的Hough空间进行直线段检测

分析图像中最近邻直线间距离和夹角的非均匀性,得到这两个参数与线段方向和长度的相关关系,并由此提出了非均匀量化Hough空间的直线检测算法NUHT (Nonuniform Hough Transform).实验结果表明,NUHT在不降低运算效率的情况下,有2倍于标准Hough变换SHT (Standard Hough Transform)的直线段检测能力,同时误报率低于SHT的1/2.     

RAID控制器中I/O调度算法研究

介绍应用于RAID控制器的I/O调度算法的设计与实现.主要目标是把来自RAID模块针对每个磁盘的具体读写请求按照响应的策略放入对应磁盘的读写I/O队列.然后根据具体请求的优先级和读写特性,对响应请求在队列中的次序进行调整或者对前后项进行合并,实现I/O请求的调度策略.     

基于主动视觉和超声的机器人目标跟踪系统

运动目标跟踪技术是未知环境下移动机器人研究领域的一个重要研究方向。该文提出了一种基于主动视觉和超声信息的移动机器人运动目标跟踪设计方法,利用一台SONY EV-D31彩色摄像机、自主研制的摄像机控制模块、图像采集与处理单元等构建了主动视觉系统。移动机器人采用了基于行为的分布式控制体系结构,利用主动视觉锁定运动目标,通过超声系统感知外部环境信息,能在未知的、动态的、非结构化复杂环境中可靠地跟踪运动目标。实验表明机器人具有较高的鲁棒性,运动目标跟踪系统运行可靠。     

路由器配置策略智能提取技术

为实现配置故障智能管理目标,提高路由器配置管理效率,提出对路由器配置文本按功能分段的算法,研究提取各分段配置策略的推理技术,构建基于可信度方法提取各分段配置策略的推理机模型。试验结果表明,它们均有94%以上的分段正确率和策略提取准确率,为构建配置故障智能管理系统做好了技术准备。     

一种改进的数据求精证明规则

提出一种改进的数据求精规则,并用关系模式进行描述。引入全局状态来描述程序所有可能的输入和输出,允许非平凡的初始化,允许前向模拟和后向模拟,能应用于消除具体模型的不确定性晚于消除抽象模型的不确定性的情况。并用实例说明了在Isabelle定理证明器中规则的应用方法。     

A single layer zero skew clock routing in X architecture

With its advantages in wirelength reduction and routing flexibility compared with conventional Manhattan routing, X architecture has been proposed and applied to modern IC design. As a critical part in high-performance integrated circuits, clock network design meets great challenges due to feature size decrease and clock frequency increase. In order to eliminate the delay and attenuation of clock signal introduced by the vias, and to make it more tolerant to process variations, in this paper, we propose an algorithm of a single layer zero skew clock routing in X architecture (called Planar-CRX). Our Planar-CRX method integrates the extended deferred-merge embedding algorithm (DME-X, which extends the DME algorithm to X architecture) with modified Ohtsuki’s line-search algorithm to minimize the total wirelength and the bends. Compared with planar clock routing in the Manhattan plane, our method achieves a reduction of 6.81% in total wirelength on average and gets the resultant clock tree with fewer bends. Experimental results also indicate that our solution can be comparable with previous non-planar zero skew clock routing algorithm. Supported in part by the National Natural Science Foundation of China (Grant No. 60876026), and the Specialized Research Fund for the Doctoral Program of Higher Education (Crant No. 200800030026)     

基于消息队列和XML的数据同步技术研究

数据同步技术一直是影响分布式计算机系统应用的一个决定性因素,在简单介绍了现有的数据同步技术的基础上,提出了采用Windows的消息队列和二进制XML编码技术相结合的数据库同步方案,给出了具有较高数据压缩比率的二进制XML编码算法,实现了在窄带网络环境下的数据同步,并对数据同步的导入导出策略进行了设计,仿真测试的结果表明该同步算法相较于传统的数据同步算法具有很好的网络传输特性及数据同步的可靠性,这些对于数据同步技术的研究,在理论与实践上都有一定的借鉴意义。     

Accurate evaluation of Green’s functions in a layered medium by SDP-FLAM

Based on local Taylor expansions on the complex plane, a method for fast locating all modes (FLAM) of spectral-domain Green’s Functions in a planar layered medium is developed in this paper. SDP-FLAM, a combination of FLAM with the steepest descent path algorithm (SDP), is employed to accurately evaluate the spatial-domain Green’s functions in a layered medium. According to the theory of complex analysis, the relationship among the poles, branch points and Riemann sheets is also analyzed rigorously. To inverse the Green’s functions from spectral to spatial domain, SDP-FLAM method and discrete complex image method (DCIM) are applied to the non-near field region and the near filed region, respectively. The significant advantage of SDP-FLAM lies in its capability of calculating Green’s functions in a layered medium of moderate thickness with loss or without loss. Some numerical examples are presented to validate SDP-FLAM method. Supported by the National Natural Science Foundation of China (Grant No. 60621002), and the State Key Development Program for Basic Research of China (Grant No. 2009CB320200)