Cheating in Visual Cryptography

A secret sharing scheme allows a secret to be shared among a set of participants, P, such that only authorized subsets of P can recover the secret, but any unauthorized subset cannot recover the secret. In 1995, Naor and Shamir proposed a variant of secret sharing, called visual cryptography, where the shares given to participants are xeroxed onto transparencies. If X is an authorized subset of P, then the participants in X can visually recover the secret image by stacking their transparencies together without performing any computation. In this paper, we address the issue of cheating by dishonest participants, called cheaters, in visual cryptography. The experimental results demonstrate that cheating is possible when the cheaters form a coalition in order to deceive honest participants. We also propose two simple cheating prevention visual cryptographic schemes.     

A correlative classifiers approach based on particle filter and sample set for tracking occluded target

Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.     

基于HLA和VEGA的海基靶场半实物视景仿真系统研究

为了在导弹试验任务中给指挥员提供决策支持,设计了一种基于HLA和VEGA的海基靶场半实物视景仿真系统。将三轴飞行转台、目标模拟器、负载模拟器等实物接入仿真系统,采用高层体系结构规范构建仿真系统的联邦架构,设计了联邦对象模型,建立了关键联邦成员的数学模型,解决了反射内存网与HLA的时间推进冲突问题,有效提高了仿真系统数据传输的实时性。采用Multigen-Creator软件建立了各个仿真实体的3D模型,利用Vega软件实现模型的渲染、场景驱动、声音仿真等。通过系统测试,结果表明：该视景仿真系统能够实时驱动各个仿真实体运行,视景画面流畅,图像刷新速率达到30帧/秒以上,满足系统实时性要求。     

Constructions and Properties of General (k,n) Block‐Based Progressive Visual Cryptography

Recently, Hou and others introduced a (2, n) block‐based progressive visual cryptographic scheme (BPVCS) in which image blocks can be gradually recovered step by step. In Hou and others’ (2, n)‐BPVCS, a secret image is subdivided into n non‐overlapping image blocks. When participants stack their shadow images, all the image blocks associated with these t participants will be recovered. However, Hou and others’ scheme is only a simple 2‐out‐of‐n case. In this paper, we discuss a general (k, n)‐BPVCS for any k and n. Our main contribution is to give two constructions (Construction 1 and Construction 2) of this general (k, n)‐BPVCS. Also, we theoretically prove that both constructions satisfy a threshold property and progressive recovery of the proposed (k, n)‐BPVCS. For , Construction 1 is reduced to Hou and others’ (2, n)‐BPVCS.]     

小波域分存和软判决恢复的隐藏技术

研究了一种把小波变换和可视密码技术相结合的信息隐藏方案,实现对灰度图像的信息隐藏。该方案把经过Arnold变换处理后的秘密信息,按照k阶线性方程求解理论产生n幅分享图片,再把n幅分享图片应用离散小波变换信息隐藏理论,分存到n幅公开图片中。提取秘密图片时,必须要大于k幅公开图片才能获得秘密图片。实验结果表明,该方案具有很强的鲁棒性,而且秘密信息不容易丢失。     

基于视觉冗余模型的码率压缩方法

提出了一种基于视觉冗余模型的码率压缩方法,它是建立在人眼视觉特性视觉冗余模型的基础上,通过与编码标准参考软件相结合,进一步压缩编码比特数。实验结果表明,在图像质量没有明显变化的前提下,此方法在视频编码标准的基础上能进一步压缩编码比特数,平均压缩率在7%～30%左右。     

基于FPGA的真三维显示器构建

通过介绍已制作的真三维显示器,解释了基于可视体素的显示技术.针对LED真三维显示分辨力较低的问题,采用了数字光投影的真三维显示方案,提出了基于FPGA的多机同步投影方法,实现了较高分辨力的空间可视体素显示.实验证明,该方法可保证真三维显示的实时性,降低系统对机械转台与光学元件的要求,为立体影像的互动提供了可靠的硬件基础...     

Double-Layer Data Embedding Scheme Based on Three-Pixel Differences

Steganography is a technique to hide the secret data into digital media without getting any unexpected notices. The traditional steganographic method, namely least significant bit (LSB) replacement, is a simple but insecure scheme. To overcome the traditional drawbacks, this paper proposes a steganographic scheme, which is called double-layer hiding method. The experimental results confirm that the proposed scheme achieves better hiding capacity with high ability of resisting security analysis.     

绿色照明及其照度计算的定量研究

本文在对绿色照明的深入理解基础上建立了绿色照明的数学模型,进一步完善了现有的绿色照明计算公式。并将计算方法应用于绿色照明的照度设计中,计算出几种光环境下绿色照明的照度范围。这是一种绿色照明设计中更能体现节能的要求、更加符合绿色照明思想的新方法。     

基于Matlab的图像自动标注

图像自动标注在检索大量数字图像时起到关键作用,它能将图像的视觉特征转化为图像的标注字信息,为用户的使用及检索带来极大的方便。研究了图像自动语义标注方法,设计并实现了基于Matlab图像自动标注系统,能够提取图像颜色特征和纹理特征,与已标注图像进行相似性度量并标注出图像语义关键词