Novel approach to SVD-based image filtering improvement

提出一种提高SVd滤波性能的新方法。基于奇异值分解滤波可以有效地分析水平(垂直)方向的图像特性。根据图像的局部方向,自适应地调整待滤波区域的形状,使重采样后局部区域中的边缘垂直或水平,再对局部区域进行奇异值分解滤波;所得的结果加权平均,得到信号估计值。将这一算法应用于图像去噪,实验结果表明,新方法可以有效地提高SVd的滤波性能。A novel approach to improve the filtering efficiency of a noisy image is proposed.Image filtering based on SVD favors the denoising in the line(horizontal)and column(vertical)direction.Based on this property,the new denoising method adapts shape and size of block to local orientation before performing SVD filtering.Through over-complete representation in overlap regions,the proposed method performs well in denoising and preserving image details.国家重点基础研究发展规划(973)(No.2007CB311005);福建省自然科学基金计划资助项目(No.A0710020);厦门大学985二期信息创新平台项目(No.2004-2008)---

Traffic Sign Detection and Recognition

道路交通标志是用图案和符号传递交通管理信息，用以管制及引导交通的一种安全管理设施。随着我国交通行业的飞快发展，城市路网愈加复杂，繁多杂乱的交通标志大大影响了人们的出行效率和出行安全。因此，作为智能驾驶辅助系统的重要组成部分，道路交通标志检测和识别系统应运而生。 作为智能驾驶辅助系统的组成部分，道路交通标志识别系统除了能帮助司机更安全地进行驾驶之外，对无人驾驶智能车辆的研究也具有重要的意义。道路交通标志识别技术是一个多学科交叉的典型的应用研究，对于涉及图像处理、计算机视觉、模式识别、人工智能等多学科交叉领域的研究具有重要的学术价值和实用价值。 本文在总结当前国内外研究成果的基础上，归纳了交通...Traffic signs, which convey the traffic management information, serve as a facilitator for traffic security management. With the development of traffic in China, more complicated the urban road network becomes, and more important the various traffic signs show on the efficiency and security of travelling people. Therefore, the traffic sign detection and recognition system, as important part of the...学位：工学硕士院系专业：信息科学与技术学院计算机科学系_计算机应用技术学号：2302007115423

A Superpixel-based Method to Demarcate the Distribution of Outdoor Building Images

提出了一种提取户外建筑目标图像中布局信息的方法.首先,基于超像素技术对所给的图像进行大致区域划分.超像素技术是基于一个测度谓词,其利用图像的基于图论的表示法来判定两区域的边界;其次,以划分后的区域(称为超像素)为单位,利用颜色、位置、纹理等信息对其进行标记.在标记纹理特征时,采用了基于3d基元的纹理识别方法.最后,定义规则整合各项标记,实现了对图像内容的划分,提取其布局信息.实验结果表明,该方法应用于常见几种布局的户外建筑目标图像都能收到较好的效果.A algorithm was proposed to grasp the rough surface layout of a outdoor building scene.It took the first steps towards segmenting an outdoor building image into regions using superpixel-based method.This mothod was based on a predicate which uses a graph-based representation of the image to measure the evidence for a boundary between two regions.Secondly,it used all of the available cues: material,location,texture gradients etc.to label the regions.A texture recognition algorithm based on 3D texton was used to capture the texture features.Finally,it combined all of the cues in order to labeling regions of the input image into coarse categories:"ground","sky",and "vertical".The results indicate that our method is able to create beautiful models for several kinds of common layout of outdoor building images.国家重点基础研究发展计划(973计划)项目(2007CB311005);福建省自然科学基金计划资助项目(A0710020);厦门大学985二期信息创新平台项