带状图像交叉区域的骨架求解算法

交叉区域的求解技术是图像骨架化中的难点,在基于无向图的图像整体骨架表示模型及算法的基础上,提出了图像交叉区域（如Ｘ形、Ｋ形等）的骨架求解算法,它根据图像交叉区域在无向图中的位置和邻接关系确定图像交叉区域的形状,并根据几何近似原理,用多边形近似方法对不同形状的交叉区域进行求解,算法充分利用图像的拓扑信息,具有速度快,了等优点,并得到了实际应用。     

用于三维图像恢复的广义点扩展函数

采用传统的摄像系统点扩展函数恢复三维图像,往往不能得到满意的结果。文中提出一种新的概念－广义点扩展函数,取代传统的摄像系统点扩展函数,用于三维图像恢复。首先给出广义点扩展函数的定义,它等于物体和场景到摄像系统的点扩展函数与摄像系统的点扩展函数的券积。然后给出物体和场景到摄像系统的点扩展函数估计。最后还给出采用广义点扩展函数恢复三维图像的实验结果。实验结果表明,采用广义点扩展函数恢复三维图像,比采用     

单电子器件的仿真

该文介绍了一种利用正统理论与Ｍｏｎｔｅ Ｃａｒｌｏ方法模拟单电子隧空器件的认真程序。该程序可模拟电子通过包含小隧道结、电容和理想电压源的电路的输运过程,利用该程序,对单库仓岛和多库仓同的单电子晶体管（ＳＥＴ）系统进行了模拟。     

基于TNC架构的可信USB存储设备管理研究

网络和移动存储设备是传播安全威胁的两个主要途径.文章介绍了TNC的体系结构和设计原理,并对TNC进行扩充,给出了一种可信USB存储设备管理方案,与TNC架构结合在一起,形成了更为完善的可信体系,从源头上阻止了网络和移动存储设备带来的安全威胁.     

基于多维告警融合的攻击目的预测系统

本文论述了基于多维告警融合的攻击目的预测系统的设计与实现.该系统利用系统状态的可证实性以及其与IDS告警之间的因果关系,先通过贝叶斯网络对已有证据进行补足完善,再利用完善后的告警信息对攻击者的攻击目的进行目的预测,从而达到了提高预测准确率的目的.     

Backbone analysis and algorithm design for the quadratic assignment problem

As the hot line in NP-hard problems research in recent years, backbone analysis is crucial for phase transition, hardness, and algorithm design. Whereas theoretical analysis of backbone and its applications in algorithm design are still at a begin- ning state yet, this paper took the quadratic assignment problem （QAP） as a case study and proved by theoretical analysis that it is NP-hard to find the backbone, i.e., no algorithm exists to obtain the backbone of a QAP in polynomial time. Results of this paper showed that it is reasonable to acquire approximate backbone by inter- section of local optimal solutions. Furthermore, with the method of constructing biased instances, this paper proposed a new meta-heuristic -- biased instance based approximate backbone （BI-AB）, whose basic idea is as follows： firstly, construct a new biased instance for every QAP instance （the optimal solution of the new instance is also optimal for the original one）; secondly, the approximate backbone is obtained by intersection of multiple local optimal solutions computed by some existing algorithm; finally, search for the optimal solutions in the reduced space by fixing the approximate backbone. Work of the paper enhanced the research area of theoretical analysis of backbone. The meta-heuristic proposed in this paper provided a new way for general algorithm design of NP-hard problems as well.     

A self-recovery fragile watermarking scheme for image authentication with superior localization

To address the problems of the inferior localization and high probability of false rejection in existing self-recovery fragile watermarking algorithms, this paper proposes a new self-recovery fragile watermarking scheme with superior localization, and further discusses the probability of false rejection （PFR） and the probability of false acceptance （PFA） of the proposed scheme. Moreover, four measurements are defined to evaluate the quality of a recovered image. In the proposed algorithm, the original image is divided into 2×2 blocks to improve localization precision and decrease PFR under occurrence of random tampering. The PFR under occurrence of region tampering can be effectively decreased by randomly embedding the watermark of each block in conjunction with a novel method of tamper detection. Compared with the current self-recovery fragile watermarking algorithms, the proposed scheme not only resolves the tamper detection problem of self-embedding watermarking, but also improves the robustness against the random tampering of self-embedding watermarking. In addition, the subjective measurements are provided to evaluate the performance of the self-recovery watermarking schemes for image authentication.     

嵌入式应用系统的可靠性设计初探

嵌入式应用系统是一个有计算机内核的智能化电子系统。集成电路的超长寿命、计算机的软件介入与智能化的控制能力,决定了嵌入式应用系统全新的可靠性设计观念。这些新观念是：基于出错概率的多值可靠性、确定应用系统的可靠性等级、建立应用系统的可靠性模型、应用系统的本质可靠性设计与可靠性控制设计。     

Learning a Maximum Margin Subspace for Image Retrieval

One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap, relevance feedback is introduced into image retrieval. With the user-provided information, a classifier can be learned to distinguish between positive and negative examples. However, in real-world applications, the number of user feedbacks is usually too small compared to the dimensionality of the image space. In order to cope with the high dimensionality, we propose a novel semisupervised method for dimensionality reduction called Maximum Margin Projection (MMP). MMP aims at maximizing the margin between positive and negative examples at each local neighborhood. Different from traditional dimensionality reduction algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which effectively see only the global euclidean structure, MMP is designed for discovering the local manifold structure. Therefore, MMP is likely to be more suitable for image retrieval, where nearest neighbor search is usually involved. After projecting the images into a lower dimensional subspace, the relevant images get closer to the query image; thus, the retrieval performance can be enhanced. The experimental results on Corel image database demonstrate the effectiveness of our proposed algorithm.     

Subband Synthesis for Color Filter Array Demosaicking

This paper presents a new algorithm for demosaicking images captured through a color filter array (CFA). The objective of the CFA demosaicking is to render a full color image from the mosaicked image. This is commonly achieved by estimating the missing color information from the surrounding observed pixels. In this paper, we integrate the observation that color images have a strong intrachannel spatial correlation in low-frequency components and a dominant interchannel correlation in the high- frequency components. A new framework is proposed to utilize this information where the missing pixels in each color channel are estimated from the wavelet subbands. A modified median-filtering operation is then applied in the subband domain. The algorithm is adaptive and produces superior full-resolution images when compared with other methods.