低勘探程度区域油气资源评价方法

目前中国油气资源勘探和开发面临后备可采储量不足，低勘探程度区域受到重视。为了提高低勘探程度区域的资源评价精度，在前人评价的基础上，通过研究并利用勘探程度较高区域的资源评价结果，求准低勘探程度区域的油气聚集量，进而模拟求出其烃排聚系数、储量密度系数、单储系数和单生系数等关键参数，提出了利用练台地质推断法对低勘探程度区域进行评价，并对该方法评价的风险进行了分析。综合地质推断法的成果更能准确反映一个盆地、坳（凹）陷或区带的油气潜力及其分布特征。     

一种分析碳酸盐岩孔隙系统数字图像的新方法

碳酸盐岩的孔隙类型多，孔径变化范围大，孔隙系统结构复杂，研究难度大。长期以来，是利用光学显微镜法、毛细管压力分析法、岩石孔隙系统复制法和图像分析仪法等方法或其中几种方法配合来研究碳酸盐岩孔隙系统。随着计算机图像技术的迅速发展和日益完善，借助该项技术通过碳酸盐岩孔隙系统数字图像来研究碳酸盐岩孔隙系统已经成为现实。文章提出一种研究碳酸盐岩孔隙系统数字图像的新方法。通过样品光薄片的光学显微镜（OM）数字图像和环境扫描电子显微镜（ESEM）数字图像二值化识别孔隙；构造孔隙度、孔隙贡献率和孔隙形状参数的计算公式用于数字图像分析，得到孔隙大小分布和孔隙形状分布。在此基础上，总结碳酸盐岩孔隙参数对其渗透率的控制作用。与传统的孔隙系统研究方法相比，该方法与计算机图像技术紧密结合，具有定量、快速的明显优势。     

抵御已知/选择明文攻击的混沌图像加密算法

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。     

彩色AC-PDP运动图像仿真系统的开发

开发了彩色AC-PDP运动图像仿真系统,通过利用本系统的运动图像仿真功能可以对现有的各种显示技术、与子场有关的各种因素进行仿真及比较,为人们开发提高彩色AC-PDP图像显示质量的新型技术及子场提供了理论上的依据;通过利用本系统的Gamma特性研究功能可以对彩色AC-PDP中视频信号的反Gamma特性进行研究,并对反Gamma相关编码进行子场逼近,为选择符合要求的子场编码提供了判据.     

刑事图像技术的应用与研究

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。     

面积坐标法构造含转角自由度的四结点膜元

以四边形面积坐标作为工具,构造了两个含转角自由度的广义协调四边形单元AQ4和lAQ4。它们通过强式分片检验,与同类单元相比,具有很高的计算精度,能消除梯形闭锁现象,有很强的抗网格畸变的能力。     

改进LSB算法及其在BMP图像中的应用

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。     

基于PCI总线的扫描电镜图像采集系统

图像采集系统是扫描电镜的一个重要组成部分，用于控制扫描电镜的扫描电源，视频图像采集，数字化与显示，电镜主控计算机与底层微机板的通讯和电镜照相，本图像采集系统基于PCI总线接口设计，硬件主要设计采用FPGA技术，实现了数字电路的模块化设计，集成度和灵活性高，目前，电镜图像卡已达到所要求的设计水平。     

利用AutoCAD编制电气CAD

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。     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

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).