Fast Structural Texture Image Synthesis Algorithm Based on Seam ConsistencyCriterion

Aiming at the problems of patch-based synthesis algorithm of structured texture images,such as discontinuity of structure,distortion of boundary,seam misalignment,and low synthesis speed,a new fast non-overlapping synthesis algorithm of texture images is proposed based on the consistency criterion of double-seam lines,thereby effectively improving the synthesis quality and speed of structured texture images.Firstly,the seamline consistency criterion considering hue,saturation,brightness and edge characteristics simultaneously is established in HSI color space that is more consistent with human visual characteristic.Then,a sub-block search strategy and a new non-overlapping splicing algorithm based on the consistency criterion of double-seam line are proposed and implemented.The experiment results show that the proposed algorithm can significantly improve the synthesis quality and speed of structured texture images in comparison with the traditional algorithms

Fragmentary fingerprint matching based on adaptive generic algorithm

在指纹图像进行采集的过程中,由于采集者本身或采集设备等各种原因会造成大量的残缺指纹图像。而这些残缺指纹图像正是影响指纹识别正确率的关键因素。在此对残缺指纹做了大量的研究,提出了二次去伪特征点的方法,并利用自适应遗传算法设计了一种基于指纹微特征信息的匹配方法。在对残缺指纹可信特征点进行人工智能的匹配,着眼于残缺指纹的全局特征进行匹配,提升了匹配的精度与速度。In the acquisition process of fingerprint images,a lot of incomplete fingerprint images may occur due to the fingerprint itself or acquisition equipment.The fragmentary fingerprint image is an important factor that affects the fingerprint recognition correctness rate.Based on enough research on fragmentary fingerprints,a diplex pseudo-discarded characteristic point method is put forward,and a matching method based on the fingerprint feature information is designed by using the adaptive genetic algorithm to match the trustworthy characteristic points of fragmentary fingerprints by artificial intelligence method.This method improved the matching accuracy and velocity.福建高校产学合作科技重大项目(0630-k42047

Particle Image Velocimetry——A whole fields technology without disturbs the flow

粒子成像测速(PIV)作为一种新的流场测试技术,不同于传统的热线、探针、雷达等测速方法,是能够在不扰乱流场的情况下(非介入),迅速地捕捉到整个流场速度信息的测量技术。它的出现为复杂流场的研究提供了更直接有效的方法。本文介绍了粒子成像测速方法的工作原理,核心技术,讨论了PIV技术的发展趋势。As an new technique for fluid flow measurement,Particle Image Velocimetry (PIV),which different from the conventional way to measure the flow velocity (pressure probes,hot wires,laser Doppler velocimety),allows for capturing velocity information of whole flow fields in fractions of a second without disturbs the flow.It brings a more efficient way to study the complex flow field.This paper introduced the principle,core technology of PIV,discussed the further development of this new technique

Research of Two Image Similarity Retrieval Algorithms

随着计算机网络和多媒体技术的发展，图像的应用日益广泛，基于内容的图像检索技术(Content-BasedImageRetrieval，CBIR)应运而生，并成为图像领域研究的热点。而目前的CBIR技术还有很大局限性，不能充分满足用户的需求。因此，对图像底层特征提取与检索技术的研究具有非常重要的意义。 本文重点研究了图像颜色特征的提取，小波变换提取图像纹理特征，融合人工智能的检索策略等问题。论文的主要工作包括基于颜色特征和纹理特征的图像检索方法研究，并在已有理论的基础上，针对具体的图像数据库，设计了一个基于颜色和纹理的图像检索实验系统，并使用Corel和Brodatz图像库对以上检索方法的有效...With the development of network and multimedia technologies, the application of image has an increasingly widespread usage. Content-Based Image Retrieval technologies have emerged and become a hot spot in the image research area. However, due to the limitations of CBIR technologies, they are still unable to fully meet the user’s requirement. Therefore, it has great significant to research on image...学位：工学硕士院系专业：软件学院_计算机软件与理论学号：2432008115247

Research on Building Recognition in Side View Images and the design of recognition system

本文主要研究在侧视可见光建筑目标图像中，位于中远距离的显著建筑目标的搜索、匹配与识别方法，以及建筑目标识别的系统的设计与实现方案。在对大量侧视建筑图像的研究和分析的基础上，本文提出一条行之有效的技术路线——首先根据建筑目标建立融合形状信息和颜色信息的特征模板，然后采用基于Halcon的多分辨率匹配方法利用形状模板的信息搜索可能的建筑目标区域，最后利用颜色模板识别建筑目标。对建筑目标特征模板的建立一方面采用基于Harr小波的提升模式的边缘提取方法提取建筑物轮廓，然后利用区域收缩技术得到其外轮廓图，最后建立基于外轮廓图的旋转变换图像金字塔，并以此作为形状模板；另一方面对模板图像的RGB和HSV空间...This paper focuses on building searching, matching and recognition with distinct building target at a distance of one mile in side imges, as well as designing a building recognition software. After substantial observation and analysis, we propose a practical approach to fullfill this task -- First, set up a compositive template inluding shape and color information of selected building. Second, use...学位：工学硕士院系专业：计算机与信息工程学院计算机科学系_计算机应用技术学号：20022801

Study on Highway Road Detection Based on Computer Vision

根据高速公路路面的基本特征,通过分道线特征点投影位置的计算,提取出了比较完整的当前车道分道线特征点。建立道路边缘灰度模型,采用gAbOr变换多分辨率的特点,对图像按方向进行滤波处理,实现道路边缘线检测和拟合。实验结果表明,所讨论的方法在工程实践中有实际应用价值。According to the basic characteristics of the road and through marginal extraction,the location of current lane line can be acquired.After calculating projection location of the lane feature points,feature points of a relatively complete current lane dividers can be distilled.Establishing the model of road edge grey scale and adopting the multi-resolution characteristics of Gabor transform,they can filter the image so that they can realize the detection and fitting of the road edge line.Experimental results show us that the method discussed in this text has a certain value in practice.福建省青年科技人才创新项目(2006F3121

Research on Content-Based Image Retrieval Using SIFT

基于内容的图像信息检索是多媒体信息检索领域中重要的组成部分，对图像的内容进行准确快速的描述一直都是图像检索技术中研究的重点和难点。传统的图像特征提取方法，基本上是围绕图像的颜色、纹理、形状和空间关系来展开的。本文提出一种基于SIFT特征的新的图像信息检索算法。SIFT特征向量是一种图像局部特征向量。它对于图像的尺度缩放、旋转、平移以及一定程度的仿射和光照变化具有良好的不变性。本文的主要内容如下： 1.系统分析和总结SIFT特征向量的特点，尝试将它应用到基于内容的图像信息检索中，并且改进传统的图像相似度度量方法。实验证实，改进后的图像距离度量更适合基于SIFT特征的图像检索。 2.采用主...Content based image retrieval (CBIR) is one of the fields of Multimedia information retrieval. The difficulty of CBIR is to properly express the contents of the images. Current CBIR systems generally make use of lower-level features like color, texture, shape and space relationship. This paper presents a new approach to extract image features for CBIR, which based on the SIFT features. SIFT featur...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：20042803

Research on Image Discriminative Representation for Image Retrieval

随着互联网的发展、社交媒体的兴起以及图像采集设备的普及，大量图像数据涌现在互联网上。图像数量的爆炸式增长，给图像检索带来了巨大的挑战。在图像检索中，通常使用词袋模型(BagOfWords,简称BOW)对图像进行描述，得到检索结果之后使用RANSAC(RANdomSAmpleConsensus，简称RANSAC)进行几何验证或者进行匹配验证实现重排序。这一检索框架存在三方面的不足:1)词袋模型完全忽略了图像中的空间结构信息，在图像的特征表示上没有充分利用空间信息增强判别性；2)面向规模较大的图像检索问题，需要相应的大规模的视觉词典，直接针对视觉词的度量方法，其计算复杂度高；3)基于RANSAC的...With the development of the Internet, the rise of social media and the popularization of image acquisition devices, a large number of images have emerged on the Internet .The explosive growth of images bring great challenge for image retrieval. In image retrieval, the Bag-of-words model is usually first used for image description ,then the returned images are proposed by RANSAC(RANdom SAmple Conse...学位：工学硕士院系专业：信息科学与技术学院_计算机应用技术学号：2302011115308

A Survey on Pedestrian Detection

行人检测是计算机视觉中的研究热点和难点,本文对2005-2011这段时间内的行人检测技术中最核心的两个问题—特征提取、分类器与定位—的研究现状进行综述.文章中首先将这些问题的处理方法分为不同的类别,将行人特征分为底层特征、基于学习的特征和混合特征,分类与定位方法分为滑动窗口法和超越滑动窗口法,并从纵横两个方向对这些方法的优缺点进行分析和比较,然后总结了构建行人检测器在实现细节上的一些经验,最后对行人检测技术的未来进行展望.Pedestrian detection is an active area of research with challenge in computer vision.This study conducts a detailed survey on state-of-the-art pedestrian detection methods from 2005 to 2011,focusing on the two most important problems:feature extraction,the classification and localization.We divided these methods into different categories;pedestrian features are divided into three subcategories:low-level feature,learning-based feature and hybrid feature.On the other hand,classification and localization is also divided into two sub-categories:sliding window and beyond sliding window.According to the taxonomy,the pros and cons of different approaches are discussed.Finally,some experiences of how to construct a robust pedestrian detector are presented and future research trends are proposed.国家自然科学基金(No.60873179);高等学校博士学科点专项科研基金(No.20090121110032);深圳市科技计划-基础研究(No.JC200903180630A);深圳市科技研发基金-深港创新圈计划(No.ZYB200907110169A);福建省教育厅基金(No.JA10196