使用基于SVM的否定概率和法的图像标注

在基于内容的图像检索中,建立图像底层视觉特征与高层语义的联系是个难题.对此提出了一种为图像提供语义标签的标注方法.先建立小规模图像库为训练集,库中每个图像标有单一的语义标签,再利用其底层特征,以SVM为子分类器,“否定概率和”法为合成方法构建基于成对耦合方式（PWC）的多类分类器,并对未标注的图像进行分类,结果以N维标注向量表示,实验表明,与一对多方式（OPC）的多类分类器及使用概率和法的PWC相比,“否定概率和”法性能更好.     

基于多特征融合与PLSA-GMM的图像自动标注

为减少图像检索中图像信息的缺失与语义鸿沟的影响,提出了一种基于多特征融合与PLSA-GMM的图像自动标注方法.首先,提取图像的颜色特征、形状特征和纹理特征,三者融合作为图像的底层特征;然后,基于概率潜在语义分析(PLSA)与高斯混合模型(GMM)建立图像底层特征、视觉语义主题与标注关键词间的联系,并基于该模型实现对图像的自动标注.采用Corel 5k数据库进行验证,实验结果证明了本文方法的有效性.     

一种图像底层视觉特征到高层语义的映射方法

基于语义内容的图像检索已经成为解决图像底层特征与人类高层语义之间“语义鸿沟”的关键。根据图像语义检索的思想,提出了一种采用支持向量机(Support Machine Vector)实现图像底层视觉特征到高层语义的映射方法,并在此基础上针对特例库实现了图像的语义标注和检索。实验结果表明,该映射方法能较好地表达人的语义,以提高图像的检索效率。     

基于视觉语义主题的图像自动标注

为减小图像检索中语义鸿沟的影响,提出了一种基于视觉语义主题的图像自动标注方法.首先,提取图像前景与背景区域,并分别进行预处理;然后,基于概率潜在语义分析与高斯混合模型建立图像底层特征、视觉语义主题与标注关键词间的联系,并基于该模型实现对图像的自动标注.采用corel 5数据库进行验证,实验结果证明了本文方法的有效性.     

基于t混合模型的自动图像标注

图像自动标注的实质是通过对图像视觉特征的分析来提取高层语义关键词用于表示图像的含义,从而使得现有图像检索问题转化为技术已经相当成熟的文本检索问题,在一定程度上解决了基于内容图像检索中存在的语义鸿沟问题.采用t混合模型在已标注好的训练图像集上计算图像区域类与关键字的联合概率分布,在此基础上,对未曾观察过的测试图像集,利用生成的模型根据贝叶斯最小错误概率准则实现自动图像标注.实验结果表明,该方法能有效改善标注结果.     

场景语义树图像标注方法

自动图像标注是一项具有挑战性的工作,它对于图像分析理解和图像检索都有着重要的意义.在自动图像标注领域,通过对已标注图像集的学习,建立语义概念空间与视觉特征空间之间的关系模型,并用这个模型对未标注的图像集进行标注.由于低高级语义之间错综复杂的对应关系,使目前自动图像标注的精度仍然较低.而在场景约束条件下可以简化标注与视觉特征之间的映射关系,提高自动标注的可靠性.因此提出一种基于场景语义树的图像标注方法.首先对用于学习的标注图像进行自动的语义场景聚类,对每个场景语义类别生成视觉场景空间,然后对每个场景空间建立相应的语义树.对待标注图像,确定其语义类别后,通过相应的场景语义树,获得图像的最终标注.在Corel5K图像集上,获得了优于TM(translation model)、CMRM(cross media relevance model)、CRM(continous-space relevance model)、PLSA-GMM(概率潜在语义分析-高期混合模型)等模型的标注结果.     

一种新的基于本体论描述的内容图像检索模型

分析了基于内容的图像检索中存在的问题,利用本体论方法建立图像底层特征本体及特定类图像本体.同时,定义了图像描述因子并建立相应的图像组合规则.最后,利用图像的底层特征进行图像检索,结合多分类支持向量机,实现图像底层特征与高层描述信息的关联,进而实现了图像语义检索,缩小了"语义鸿沟"对基于内容的图像检索的影响.实验结果表明本模型能够提高基于内容的图像检索的准确率,同时,经过3～5次反馈,可以实现语义检索功能.     

基于遗传算法和 FCM 的图像自动标注*

为了缩减图像底层视觉特征与高层语义之间的“语义鸿沟”及减少聚类的不稳定性,论文提出了一种基于遗传算法和FCM的图像自动标注方法。该方法首先提取图像的颜色和纹理特征,然后运用遗传算法和FCM 相结合的方法对图像进行聚类。最后通过支持向量机学习训练库的图像特征构造简单的多类支持向量机模型实现图像的自动标注。实验表明,该方法具有很好的图像标注性能。     

基于MPEG-7和MM混合模型的图像自动标注算法

为了弥补图像低层视觉特征和高层语义之间的"语义鸿沟",改善图像自动标注的性能,提出了基于多媒体描述接口(MPEG-7)和MM(Mixture Model)混合模型的图像标注算法。该算法采用MPEG-7标准推荐的颜色和纹理描述子提取图像的低层视觉特征,通过MM混合模型建立低层特征到高层语义空间的映射,实现了基于图像整体低层特征的多标签图像自动标注。通过在corel图像数据集上的一系列实验测试验证了该方法的可行性和有效性。     

SVM用于基于块划分特征提取的图像分类

在基于内容图像检索中,图像的底层视觉特征和高层语义概念之间存在着较大的语义间隔。使用机器学习方法学习图像特征,自动建立图像类的模型成为一种有效的方法。本文提出了一种用支持向量机(SVM)实现自然图像自动语义归类的方法,基于块划分聚类得到特征向量作为SVM训练样本,实现语义分类器。由于参与聚类的是某类图像所有块的特征,提取的特征更能反映某一类图像特征。实验证明这种方法是有效的。     

Context-based Space Filling Curves

A context-based scanning technique for images is presented. An image is scanned along a context-based space filling curve that is computed so as to exploit inherent coherence in the image. The resulting one-dimensional representation of the image has improved autocorrelation compared with universal scans such as the Peano-Hilbert space filling curve. An efficient algorithm for computing context-based space filling curves is presented. We also discuss the potential of improved autocorrelation of context-based space filling curves for image and video lossless compression.     

科学仪器远程操作中样品图像

提出“金字塔”式网络传输模型,将图像按质量分成不同等级,根据用户网络速度发送不同等级的图像,使不同带宽用户最大程度上同步获取到图像。实验证明,该分级模型使不同带宽的用户获取图像时间都在几百个毫秒左右,解决了各用户由于网络速度不同或网络速度不稳定而造成获取图像不同步的问题。     

信道自适应主动块低频分量丢弃数字图像传输技术

为减少图像传输的数据量,满足信道带宽的要求,在图像发送端以块为单位对图像进行划分,利用离散余弦变换(DCT),按照一定的规则主动丢弃部分块的低频分量,而在图像接收端通过图像重建技术对丢弃的图像数据进行恢复,从而再现原图像。实验结果表明这种数字图像传输技术改善了DCT图像质量。     

Automatic Generation of Virtual Woodblocks and Multicolor Woodblock Printing

In this paper, we study a method to synthesize a multicolor virtual woodblock print by using several virtual woodblocks. It consists of two sections: carving and printing, to synthesize a virtual print. In the carving section, virtual woodblocks are generated by a user with supporting of an automatically carving method based on feature extraction of a gray value image. And woodblocks are also generated automatically by using a full-color image as a draft. In the printing section, a "paper sheet", a "printing brush" and "ink" are prepared in addition to the "woodblock" in the virtual space and the user synthesizes a woodblock print interactively. As the printing factors, a color of ink, a moisture value and a grain change the finish of the print. Using several virtual woodblocks and printing to a paper sheet in succession, a printing image of each woodblock is combined based on the printing factors and a multicolor virtual prints is synthesized.     

A digital image system for atmospheric research

This paper describes the architecture of a medium scale digital image processing system developed as a research tool for analysis of meteorological data. The system is also being used for research on efficient image processing systems. Four qualitative performance measures for any image processor are introduced with specific application to the present machine. Preliminary results with noise reduction algorithms in satellite data are presented. Lastly, the versatility of the machine as a test bed for architectural studies of the computational structure of image processors with a microprogrammable control unit is discussed.     

External Memory View-Dependent Simplification

In this paper, we propose a novel external-memory algorithm to support view-dependent simplification for datasets much larger than main memory. In the preprocessing phase, we use a new spanned sub-meshes simplification technique to build view-dependence trees I/O-efficiently, which preserves the correct edge collapsing order and thus assures the run-time image quality. We further process the resulting view-dependence trees to build the meta-node trees, which can facilitate the run-time level-of-detail rendering and is kept in disk . During run-time navigation, we keep in main memory only the portions of the meta-node trees that are necessary to render the current level of details, plus some prefetched portions that are likely to be needed in the near future. The prefetching prediction takes advantage of the nature of the run-time traversal of the meta-node trees, and is both simple and accurate. We also employ the implicit dependencies for preventing incorrect foldovers, as well as main-memory buffer management and parallel processes scheme to separate the disk accesses from the navigation operations, all in an integrated manner. The experiments show that our approach scales well with respect to the main memory size available, with encouraging preprocessing and run-time rendering speeds and without sacrificing the image quality.     

Field‐aligned Quadrangulation for Image Vectorization

Image vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature‐aligned quad‐dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field optimization technique by encoding the color gradients, sidestepping the explicit computing of salient image features. We further compute the anisotropic scales of the directional field by accommodating the distance among image features. Our method is fully automatic and efficient, which takes only a few seconds for a 400×400 image on a normal laptop. We demonstrate the effectiveness of the proposed method on various image editing applications.     

数字监控中自动报警系统的设计与实现

基于数字图像处理的监控系统是利用先进的计算机技术,采用数字图像处理技术、多媒体技术以及网络技术,实现时监控现场的自动监控管理,该系统可以实现无人值守的全自动监控,可以大大提高工作效率、节省费用及提高信息自动化水平,具有很大的经济效益和社会效益。     

基于VC++和VFW的视频图像算法接口

采用VC++6.0语言结合VFW库设计了摄像头视频图像的二维数组算法接口,以方便各类图像检测算法调用,设计了空白血型卡定位测试算法,验证了算法接口的有效性。利用VC++2005中的CImage类设计了图像保存功能的动态链接库,使得在VC++6.0中可以实现JPG等格式图像的保存,实现了检测结果文档的保存和打印。     

Illuminant Aware Gamut‐Based Color Transfer

This paper proposes a new approach for color transfer between two images. Our method is unique in its consideration of the scene illumination and the constraint that the mapped image must be within the color gamut of the target image. Specifically, our approach first performs a white‐balance step on both images to remove color casts caused by different illuminations in the source and target image. We then align each image to share the same ‘white axis’ and perform a gradient preserving histogram matching technique along this axis to match the tone distribution between the two images. We show that this illuminant‐aware strategy gives a better result than directly working with the original source and target image's luminance channel as done by many previous methods. Afterwards, our method performs a full gamut‐based mapping technique rather than processing each channel separately. This guarantees that the colors of our transferred image lie within the target gamut. Our experimental results show that this combined illuminant‐aware and gamut‐based strategy produces more compelling results than previous methods. We detail our approach and demonstrate its effectiveness on a number of examples.