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).     

实时Motion JPEG2000视频编码系统设计

介绍了基于ADV202 JPEG2000编码芯片的Motion JPEG2000视频编码系统,该系统可实现SMPTE274M的实时编码,支持失真/无失真编码,与标准完全兼容.给出了系统硬件结构和软件流程设计,提出了一种利用帧间相关性减少编码计算量的码率控制方法.     

一种新型的多功能照相胶片影像质量评价方法

本设计了一种新型的多功能照相胶片感光性能和影像质量评价方法。这种方法的主要特点的快速、方便并有满足 实用要求的精确度。该方法仅使用一个测试标板，就可以很容易地测定出照相胶片的感光性能、分辨率、均方根粒度和密度振幅响应（DAR）值等多种表征影像质量的参数。本简要介绍该方法并给出试验结果及其与传统测试方法的比较和讨论意见。     

基于水印的图像认证和完整性保护技术

数字水印技术的发展为解决图像认证和完整性保护问题提供了新的思路。对用于篡改检测和图像认证的水印技术做了综述。数字水印技术根据其识别差错的能力分为四种类型:易损水印、半易损水印、混合水印和自嵌入水印。最后还对水印认证技术的安全性问题进行了讨论。     

一个基于相邻像素兼容度的模糊加权平均滤波器

在文献[1]的基础上，提出几个改进的模糊加权平均滤波器。本文的方案不仅同时考虑了相邻像素对中心像素的兼容性以及中心像素对相邻像素的兼容性，而且还考虑到了权系数对局部环境的适应性。实验结果表明，该方法相比文献[1]中的模糊加权平均滤波器以及标准的均值滤波器、中值滤波器在噪声消除与边缘保留方面具有更好的性能。     

区域分割法辅助计算复杂图像面积

介绍计算具有复杂边缘轮廓的图像面积的区域分割法。采用鼠标多边形作图法近似圈定待处理的图像区域。本文由格林定理出发得到有限连续边界与其包围区域面积之间的函数关系,并且应用这一函数关系得出多边形与其包围区域面积的数学关系,近似得到图像区域面积。文中以烟幕图像为例对上述结论进行了验证。文章最后给出了在VC++环境下实现多边形分割的部分源代码。     

变换域数字水印处理技术

数字水印是信息安全领域的一项新技术,给出了相对明确的定义。着重分析了变换域数字水印系统的特征及常见攻击,给出了一些相应的对策。最后指出变换域水印的重要问题,即频率的选择问题。     

基于数据挖掘的OLAP分析技术及应用

数据仓库和数据挖掘技术是目前信息技术研究的热点问题之一,介绍了数据挖掘(data mining)、数据仓库(datawarehouse)及联机分析处理(OLAP)技术。并以零售业决策支持系统为例,介绍了该系统的体系结构、数据仓库的设计、系统实现关键技术及各子系统功能,着重论述了如何利用OLAP技术实现企业决策支持系统。     

飞行目标3维姿态测量的新方法

针对传统光测方法通常用于测量目标的点运动轨迹,而难以获得目标的3维姿态参数的情况,提出用数字图像处理手段,对目标图像建立特征点,结合特定的算法,得出目标的俯仰角、偏航角、滚动角、漂移量等3维参数,从而获取更多的目标姿态参数的新方法。     

基于主体外部轮廓的照片分割算法

在实际应用中常常需要将人像从照片的背景中有效地分割出来，通常的做法是通过提取照片中人像各部分特征来实现分割，其缺陷是计算复杂度较大，分割效果受各种干扰因素影响很大。现提出了一种基于主体外部轮廓信息的照片分割算法，通过梯度锐化、边缘保护、临近像素点相似度比较来确定图像的边界，该算法对于具有相对均匀背景的照片具有较高的计算效率。