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31.
论文在对现有一类典型图像混沌加密算法的分析基础上,提出了一种改进的图像混沌加密算法。该算法引入小波变换,可以有效地克服一些混沌加密算法不能抵御已知/选择明文攻击的缺陷。 相似文献
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刑事图像技术是刑事科学的重要组成部分:是检验、固定痕迹物证的一种方法。刑事图像的重大应用在于扩大人类的视野,显示肉眼看不到或看不清的重要细节,以便揭露和证实犯罪。 相似文献
34.
Recently, preemption techniques have attracted considerable attention as a means to provide differentiated quality of service
in optical burst switching (OBS) networks. This paper is focused on the analysis of preemption probabilities for bursts within
the same priority class. As proposed by Vokkarane and Jue ((2003)* IEEE J Select Areas Commun 21(7): 1198–1209) an incoming
burst will preempt the burst in service, within the same priority class, if the residual length of the burst in service is
smaller than the incoming burst length. For a general case with wavelength conversion, the preemption probability of contending
bursts with a generic service distribution, not necessarily exponential, is analyzed. First, we show that the size distribution
for the preempting bursts is shifted to larger values, in comparison to the original burst size distribution. Second, we obtain
an upper and lower bound for the preemption probability. Finally, the asymptotic behavior of the OBS switch is analyzed showing
that preemption will always occur for a very large number of wavelengths. 相似文献
35.
首先分析了BMP图像文件格式,然后根据传统LSB算法在BMP图像文件中应用,提出一种改进的LSB隐藏算法,提高了伪装图像质量。最后通过仿真验证了该算法的优越性。 相似文献
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介绍如何利用AutoCAD开发适合电气专业使用的CAD系统,通过编制电气CAD的功能菜单,构造电气元件库,增强CAD的专业性能。编制电气CAD可以有效地统一本单位电气制图标准,方便电气工程师使用CAD进行专业设计。 相似文献
38.
Automatic fog detection and estimation of visibility distance through use of an onboard camera 总被引:2,自引:0,他引:2
Nicolas Hautiére Jean-Philippe Tarel Jean Lavenant Didier Aubert 《Machine Vision and Applications》2006,17(1):8-20
In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses.
Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition.
Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling.
Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports.
Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety). 相似文献
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一种新颖的基于非压缩数字视频的水印盲检测算法 总被引:10,自引:0,他引:10
数字水印是一种嵌入到多媒体数据中用来进行版权标识的工具。在众多的宿主媒体中,数字视频因具有隐藏容量大、透明性好、鲁棒性强等诸多优点而受到日益广泛的关注。但是很多文献中提到的视频水印都是从数据流中提取单帧图像进行处理,这类算法与静态图像的水印方法如出一辙,没有充分利用视频文件的各种特性。而且对帧平均、视频压缩等常见的运动图像攻击方法十分敏感。针对这些问题,本文以非压缩视频文件为实验对象,结合人类视觉模型和彩色图像场景分割的方法,提出并实现了一种基于视频时间轴的数字水印盲检测算法。实验结果表明算法有效实用。 相似文献