基于组合欧拉向量与边缘方向直方图的图像检索方法

在图像数据库中,如何有效检索和查询图像是一个重要的研究内容.文中提出一种结合组合欧拉向量与边缘方向直方图( EOH)的图像检索方法.首先,从边缘图像中提取组合欧拉向量特征进行图像检索(EEXO算法),其次,为更好地区分不同形状但欧拉特征相近的图像,将EEXO算法与EOH算法相结合提出EEXOEOH图像检索算法.实验结果表明,EEXOEOH算法与其它4种算法相比,具有较好的检索效率.     

利用差分矩阵进行基于内容的图像检索

随着大容量图像数据库的广泛应用,基于内容的图像检索(CBIR)技术成为对其进行管理和检索的有效手段。文中提出了一种基于灰度变化进行基于内容的图像检索的方法,利用差分概念提取出图像的差分矩阵,再从中提取特征进行度量。给出了对自然图像库检索的实验结果,实验表明,采用该方法比空间颜色直方图与共生矩阵等方法能取得更好的检索效果。与颜色空间直方图和灰度共生矩阵的比较实验证明差分矩阵的方法在速度和结果上都有比较好的效果。     

结合距离变换和隐层图词包的手绘图像检索方法

随着触屏设备的广泛普及,基于手绘的图像检索技术受到了越来越多的关注.针对HOG,SIFT,RST-HELO等传统图像描述子在基于手绘图像检索领域的局限性,提出一种基于卷积神经网络构建隐层图词包特征描述子的手绘图像检索方法.首先对数据库图像提取边缘概率图;其次在边缘概率图上计算Chamfer距离变换图像,通过对距离变换图像提取隐层图词包特征构建预分类检索.在Flickr15K数据集上对文中方法进行了实验,证明基于隐层图词包特征描述子的检索效果比RST-HELO等传统方法有了显著提高;从图像预处理和特征描述子两方面对SBIR进行了改进,实验结果表明,文中方法具有更高的准确率.     

基于形状特征的图像检索技术研究

随着图像信息数量的飞速增长,人们迫切需要对大量的图像信息进行快速、有效的检索。因此,研究者们提出了许多图像检索新技术。阐述了图像检索技术的发展过程;分析了基于形状特征的图像检索技术研究现状和局限性;着重从特征提取、高层语义和形状特征的关联、高维索引技术等方面研究了基于形状特征的图像检索的发展趋势。     

基于九分块的颜色直方图图像检索算法

随着社会和科技的发展,人们对基于内容的图像检索的要求越来越高,但因研究起点较晚,技术还不是很成熟。文中就图像检索所用到颜色、纹理、形状、轮廓的基本颜色特征中比较重要的颜色特征为主要研究对象,从传统的基于全局颜色直方图及后来发展的一些改进的颜色直方图等思路出发,提出了一种基于九分块的颜色直方图方法,提高了图像检索的效率。     

基于形状特征的图像检索技术研究

随着图像信息数量的飞速增长，人们迫切需要对大量的图像信息进行快速、有效的检索。因此，研究者们提出了许多图像检索新技术。阐述了图像检索技术的发展过程；分析了基于形状特征的图像检索技术研究现状和局限性；着重从特征提取、高层语义和形状特征的关联、高维索引技术等方面研究了基于形状特征的图像检索的发展趋势。     

利用差分矩阵进行基于内容的图像检索

随着大容量图像数据库的广泛应用,基于内容的图像检索(CBIR)技术成为对其进行管理和检索的有效手段.文中提出了一种基于灰度变化进行基于内容的图像检索的方法,利用差分概念提取出图像的差分矩阵,再从中提取特征进行度量.给出了对自然图像库检索的实验结果,实验表明,采用该方法比空间颜色直方图与共生矩阵等方法能取得更好的检索效果.与颜色空间直方图和灰度共生矩阵的比较实验证明差分矩阵的方法在速度和结果上都有比较好的效果.     

文本检索方法驱动的海量图像数据库目标匹配研究

针对当前基于文本检索方法的图像目标对象匹配技术无法适应海量图像数据库检索的问题,本文提出一种有效可行的海量图像数据库的检索方法,并给出了该系统的构建框架。用户通过在图像中选择一块区域作为检索的目标对象提交给系统,它将从图像数据库中检索出包含有相同或相似目标对象的图像,将其排序后返回给用户。实验表明,本文提出的方法具有检索准确率高、响应时间短等特点,是一种有效的海量图像数据库检索方法。     

基于RBFN的交互式图像检索方法

相关反馈技术是近年来图像检索中的重要研究方向,它有效地缩短了用户高层语义和图像底层视觉特征的差距,大大提高了系统的检索精度。文中从机器学习的角度出发,提出了一种基于RBFN的相关反馈算法。同时,为了方便用户对检索结果的标记,将模糊逻辑引入到图像检索中。即:用户对检索结果标记为相关图像、模糊相关图像和不相关图像,利用这些反馈信息动态地建立RBFN的结构,并进行检索,这个过程反复进行直到用户得到满意的结果。实验表明,这种方法在图像检索中具有更好的性能和更强的推广能力。     

一种基于颜色直方图的图像检索方法

随着社会和科技的发展,人们对基于内容的图像检索(CBIR)的要求越来越高,但因研究起点比效晚,技术上还不是很成熟.文中就图像检索所用到颜色、纹理、形状、轮廓的基本颜色特征中比较重要的颜色特征为主要研究对象,从传统的基于颜色直方图及其后来发展的主要面积直方图和平均面积直方图等思路出发,分析其优缺点,提出一种基于图像分割主要面积直方图方法,提高了图像检索的性能.     

On stability of signature-based similarity measures for content-based image retrieval

Retrieving similar images from large image databases is a challenging task for today’s content-based retrieval systems. Aiming at high retrieval performance, these systems frequently capture the user’s notion of similarity through expressive image models and adaptive similarity measures. On the query side, image models can significantly differ in quality compared to those stored on the database side. Thus, similarity measures have to be robust against these individual quality changes in order to maintain high retrieval performance. In this paper, we investigate the robustness of the family of signature-based similarity measures in the context of content-based image retrieval. To this end, we introduce the generic concept of average precision stability, which measures the stability of a similarity measure with respect to changes in quality between the query and database side. In addition to the mathematical definition of average precision stability, we include a performance evaluation of the major signature-based similarity measures focusing on their stability with respect to querying image databases by examples of varying quality. Our performance evaluation on recent benchmark image databases reveals that the highest retrieval performance does not necessarily coincide with the highest stability.     

支持基于内容检索的图像数据模型的设计

以面向对象的多媒体数据库系统Jasmine为平台,设计具有基于内容图像检索功能的面向对象数据模型,作为数据库的引擎,实现了一个支持基于内容检索技术的图像数据库系统。     

A region-based image database system using colour and texture

In this paper, a region-based image database system is presented. When an image is entered into the database it is first clustered into similar looking regions using the local colour and texture properties of the image. The mean colour and texture properties of these regions along with their location and size are then stored as an index into that image.To query the database, the user specifies an object on which the same texture and colour properties are calculated. A neural network is trained on these features and then used to search through the indices of the database images. All similar looking regions in the images are shown as the results to the query.     

基于双重零水印的数据库版权保护

数据库零水印具有二义性,可能引起数据库的版权纠纷。为此,提出一种数据库版权图像零水印算法。以零宽度不可见字符作为水印符号,将版权图像嵌入宿主数据库,构造一重数据库零水印,同时使用字符型数据Unicode编码提取二重数据库零水印。实验结果表明,该算法可以提高数据库版权保护能力。     

An efficient ear localization technique

This paper proposes an efficient technique for automatic localization of ear from side face images. The technique is rotation, scale and shape invariant and makes use of the connected components in a graph obtained from the edge map of the side face image. It has been evaluated on IIT Kanpur database consisting of 2672 side faces with variable sizes, rotations and shapes and University of Notre Dame database containing 2244 side faces with variable background and poor illumination. Experimental results reveal the efficiency and robustness of the technique.     

Image indexing and retrieval based on color histograms

While general object recognition is difficult, it is relatively easy to capture various primitive properties such as color distributions, prominent regions and their topological features from an image and use them to narrow down the search space when attempts to retrieving images by contents from an image database are made.In this paper, we present an image database in which images are indexed and retrieved based on color histograms. We first address the problems inherent in color histograms created by the conventional method, and then propose a new method to create histograms which are compact in size and insensitive to minor illumination variations such as highlight, shape, and etc. A powerful indexing scheme where each histogram of an image is encoded into a numerical key, and stored in a two-layered tree structure is introduced. This approach turns the problem of histogram matching, which is computation intensive, into index key search, so as to realize quick data access in a large scale image database. Two types of user interfaces, Query by user provided sample images, and Query by combination of the system provided templates, are provided to meet various user requests. Various experimental evaluations exhibit the effectiveness of the image database system.     

基于本体的关联规则挖掘算法研究

在图像数据库中,针对图像的检索方法很多,但以传统的基于内容的图像检索方法效率低,而且误差较大.提出一种基于OBFM（ontology_based feedback model）方法首先得到基本相似图像库,从中提取相应的特征元素,并在此基础上进行关联规则挖掘.该算法充分考虑了图像具有空间可重复性的特点,从而提高了图像检索的准确率.     

用VB.NET设计图形数据库程序

讲述了使用VB．NET设计图形数据库程序的方法和技巧。分别介绍了图形数据库记录的插入、浏览、修改等内容，重点讨论了如何向数据库写入图片以及从数据库中读出图片。这些技巧在开发数据库应用程序中很有实用价值。     

Secure authentication watermarking for localization against the Holliman–Memon attack

Authentication watermarking schemes using block-wise watermarks for tamper localization are vulnerable to the Holliman–Memon attack. In this paper, we propose a novel method based on the Wong’s localization scheme (Proceedings of the IS&T PIC, Portland) to resist this attack. A unique image index scheme is used for computing the authentication signature that is embedded in the least significant bit-plane of the block. The informed detector estimates the correct image index by using the side information about the watermarked image. The image index estimation from the fake image can definitely be an alternative to keeping a directory of image indices. So it is not necessary to manage the database of image indices for the verification purpose. The authenticity measure is defined to quantify the attack severity by taking the connectivity among possible authentic blocks into consideration. There are more blocks verified as authentic when this measure is high for a fake image constructed using this attack. As such, the blocks for a fake image can be chosen from a reduced number of database images. The blocks from any such image are to be connected with each other to maximize the authenticity measure. Thus, the attacker’s task to generate a fake image of reasonable perceptual quality becomes increasingly difficult. With the proposed method there is no loss or ambiguity in localization after the Holliman–Memon attack and content tampering in an image. The localization accuracy in the proposed method is demonstrated by the simulation results and is equal to the chosen block size, similar to the Wong’s scheme.     

基于风格迁移纹理合成与识别的构造式信息隐藏

传统的信息隐藏算法大都通过修改载体达到隐藏秘密信息的目的,但不可避免地会在载体数据中留下修改痕迹,故常难以抵抗隐写分析技术的检测,为此无载体信息隐藏应运而生.无载体信息隐藏并非不使用载体,而是不对载体数据进行修改.为了提高无载体信息隐藏算法的隐藏容量和鲁棒性,提出了一种基于风格迁移纹理合成与识别的构造式信息隐藏算法.该算法首先选取不同类别的自然图像和纹理图像分别建立内容图像库和纹理风格图像库,并根据内容图像库中自然图像的类别构建二进制码的映射字典;其次为了接收方能够从含密图像中提取出秘密信息,需要构建带标签的纹理图像库,并将其作为训练集输入到卷积神经网络中,通过迭代训练获得纹理图像识别模型.在秘密信息隐藏时,根据秘密信息片段选择对应类别的自然图像,并按照一定的顺序组合成含密拼接图像,随后从纹理图像库中随机选择一张纹理图像,通过风格迁移的方法将含密拼接图像转换成含密纹理图像,从而完成秘密信息隐藏过程.在信息提取过程中,通过纹理图像识别模型可准确识别出含密纹理图像原本对应的图像类别,再对照映射字典即可提取出秘密信息.实验结果表明,所提算法生成的含密纹理图像具有良好的视觉效果,秘密信息隐藏容...