Content-based image retrieval using color vector angle difference histogram

Abstract

This paper presents an innovative method to represent an image for image retrieval in Content-Based Image Retrieval (CBIR), using a color vector angle differences histogram approach (CVADH), which is different from the existing histograms, such as color histograms, gray level co-occurrences (GLCM), color distribution entropy (CDE), or just counting the frequency number of pixels or neighbors. In contrast to other methods, the CVADH takes account of the color difference and spatial information of two pixels in RGB color space. Furthermore, it directly leverages color clues to extract shape features to show differences given different backgrounds. Experimental results show that the scheme is more efficient than traditional ones that have been developed for CBIR.     

基于双级特征提取与度量的图像检索算法

目的 针对单一低层特征在语义属性中的信息易丢失,导致其对图像描述能力不强,使其检索精度不佳的问题,结合颜色矩（CM）、角径向变换描述符（ART）和边缘直方图（EH）等3种特征,定义一种双级特征提取与度量的图像检索方案。方法 首先,将图像转换为HSV色彩空间,并将其分割为若干个非重叠子图像,通通过计算每个子图像的均值、标准差和偏斜度来表征CM;再利用Euclidean距离,对查询图像和数据库图像的CM进行提取与度量,将输出的检索结果标记为一个图像集。随后,提取查询图像与图像集中每个目标的ART和EH特征;利用Euclidean距离分别度量查询图像与图像集中目标的ART与EH的相似性;最后,对ART与EH的加权组合,输出相似性最高的检索图像。结果 实验表明,与当前常见的检索算法比较,文中算法具有更高的检索精度,表现出更优异的Precision-Recall曲线。结论 所提算法具有良好的检索准确度,在信息处理、包装商标等领域具有一定的参考价值。     

基于分块主色和形状特征的彩色图像检索

提出一种新的基于分块主色和形状特征的图像检索算法。图像首先被划分为不同分块,并提取分块主色,然后采用主色直方图作为图像的颜色特征。同时,提出采用平坦度和凹凸度来描述图像的形状特征,在分析平坦度和凹凸度统计特性的基础上,提出了新的量化的方法,并采用量化后的特征直方图作为图像的形状特征。试验结果表明,本文方法在图像的相似性检索时是很有效的,并具有较高的检索效率。     

一种新的基于颜色矢量角的图像空间描述符

在分析利用颜色直方图进行图像检索时存在问题的基础上,提出了一种新的图像空间描述符.首先利用颜色矢量角的特性将图像分为边缘区和平滑区两部分,然后,针对两种区域的不同分布特点,综合利用图像的边缘信息、形状信息及空间分布特性,采用两种不同的描述符--方向颜色矢量角直方图和空间联合分布熵分别来提取图像的边缘区和平滑区的分布特征.实验结果表明,将其用于图像检索,取得了很好的检索效果.     

Silver Sulphide Formation During Thiosulphate Sensitization

Emulsions prepared with an inert gelatin have been sensitized with sodium thiosulphate labelled with radioactive ³⁵S. An analytical technique similar to that used by Frieser and Ranz¹ has been used to measure the amounts of silver sulphide formed. The breakdown of thiosulphate has been shown to follow first order reaction kinetics at a rate proportional to the free silver ion concentration in the emulsion to the power of 0.8.     

基于内外边缘颜色特征的图像检索算法

算法的基本思路是提取边缘部分的颜色特征进行图像检索,将边缘分为内外边缘区别对待,加大内边缘(对应目标部分)的比重,通过多尺度多结构元的数学形态学方法实现。通过设置内外边缘的权重充分考虑了目标的重要性,克服了全局颜色直方图不能反映空间信息的缺陷。实验结果表明,该算法有效地提高了检索系统的效率。     

基于颜色信息与空间特征的自适应商标检索算法

目的为了增强商标检索技术对商标特征的描述能力,改善其在外来干扰下的检索精度与鲁棒性。方法提出一种基于颜色与空间特征自适应结合的商标检索算法。首先,引入主颜色描述符(DCD),将其作为颜色特征检测器,并在颜色特征提取时嵌入k-均值聚类算子,增强颜色区域,准确提取颜色特征。随后,每个商标被量化为8个显色的最大值,以便提取每个颜色分量中的空间分布信息。然后,通过利用不同的权重来平衡颜色与空间特征的重要性,定义一种基于模糊直方图分析技术,计算每个商标自适应系数,以准确描述彩色商标的图像特征。最后,通过Euclidean距离进行相似度量,输出检索到的商标。结果实验结果表明,与当前商标检索方法相比,所提算法具有更高的检索精度与鲁棒性,呈现出更理想的P-R曲线,在召回率为0.7时,其检索准确率仍可达到90%。结论文中检索方法具有较高的检索精度,在包装商标检测、商标版权保护等领域中具有良好的应用价值。     

利用粗糙集和属性直方图的图像增强方法

利用粗糙集理论进行图像增强,子图的划分是关键。属性直方图是对直方图概念的推广,是一种由先验知识约束的直方图;将它用于子图的划分,在此基础上提出了一种基于粗糙集理论和属性直方图的图像增强方法。该方法利用属性直方图的 Otsu 算法确定灰度阈值,根据灰度阈值利用不可分辨关系,将图像划分为背景子图、目标子图和噪声子图,对去噪后背景子图和目标子图进行增强变换,并将它们合并得到增强图像。将该方法用于一种海底小目标图像增强。实验结果表明该方法处理增益为 11dB,明显地增强了图像,且不损害图像的边缘。该方法适用于图像有某种先验知识的场合。     

Image contrast enhancement using histogram equalization with maximum intensity coverage

The histogram equalization process is a simple yet efficient image contrast enhancement technique that generally produces satisfactory results. However, due to its design limitations, output images often experience a loss of fine details or contain unwanted viewing artefacts. One reason for such imperfection is a failure of some techniques to fully utilize the allowable intensity range in conveying the information captured from a scene. The proposed colour image enhancement technique introduced in this work aims at maximizing the information content within an image, whilst minimizing the presence of viewing artefacts and loss of details. This is achieved by weighting the input image and the interim equalized image recursively until the allowed intensity range is maximally covered. The proper weighting factor is optimally determined using the efficient golden section search algorithm. Experiments had been conducted on a large number of images captured under natural indoor and outdoor environment. Results showed that the proposed method is able to recover the largest amount of information as compared to other current approaches. The developed method also provides satisfactory performances in terms of image contrast, and sharpness.     

基于区域主色特征的目标匹配算法

图像彩色特征被广泛应用于内容检索系统(CBIR)与目标识别系统中,如何描述获取区域图像彩色特征是应用颜色特征的基础.论文基于HSV色彩空间中色调量化直方图定义了目标区域主色特征,并综合目标区域主色均值距离与主色直方图相似性给出了区域颜色之间距离表达.同时利用算法对显微镜染色细胞图像中的细胞颜色进行了有效区分,得到了好的匹配结果.     

模拟频域滤波重构直方图均衡的图像增强方法

针对传统图像增强方法的不足,提出一种基于模拟频域滤波重构直方图均衡的图像增强方法.将频率域滤波的思想引入空间域直方图运算当中,在模拟频率直方图统计中进行频率信息的统计,利用这些频率信息建立模拟频率域坐标,进行模拟频域滤波,对滤波处理后的直方图进行均衡化处理.实验表明:与传统方法相比,该算法优化了灰度级的动态分布范围,能得到更清晰的增强效果,且在图像中没有视觉明显的噪声放大.     

纹理贴图模型的彩色截面轮廓生成算法研究

针对彩色3D打印彩色轮廓生成问题,本文提出一种基于纹理贴图模型的彩色轮廓生成算法。根据平面投影法建立纹理和三维模型的映射关系,接着对该模型进行切片处理取得轮廓顶点的几何信息和纹理信息;并根据轮廓顶点和纹理图片的映射关系,插值出顶点间色彩信息;同时给出一种内外轮廓的快速识别算法,并提出一种基于偏置算法的彩色轮廓偏置方法,形成颜色厚度,消除阶梯效应。     

基于色彩空间变换的电润湿电子纸色彩校正

电润湿电子纸采用减色混色系统进行色彩显示,色域较小,容易发生色彩失真,且依赖环境光的漫反射,亮度不足。为解决这些问题,提出一种基于彩色电润湿的色彩空间转换和图像自适应增强算法。该算法将图像从RGB色彩空间转换到HSV空间,并使用CLAHE对饱和度进行均匀分布处理,改善色彩表现。亮度通道通过引导滤波和改进的Retinex算法进行增强,保留细节与边缘信息,使电润湿电子纸在相同光照下依旧保持真实视觉效果。实验结果表明,该算法在PSNR、SSIM、FSIM和FSIMc上分别提高了19%、10.8%、19.19%和19.54%,显著优化电润湿电子纸的显示效果,为其市场化应用提供有力支撑。     

IFS分形码的快速图像检索算法

图像经分形编码后产生IFS分形码,它可被用来进行图像检索操作。针对图像检索的特点,将分形码中的位置参数替换为相对距离与方向系数。定义了分形码间的距离以及图像间的分形码距离,并取出分形码距离最小的前门幅图像作为检索结果,由此提出了基于IFS分形码的快速图像检索算法。从时间复杂性上分析,利用本文算法所需的检索时间与值域块的个数有关。实验结果表明,相对缩放与旋转变化,算法对位移与亮度变化具有较强的稳定性,其分形码距离的均值仅为14.07和20．05;并可检索到具有一定相似性的图像,且类间与类内分形码距离约相差8,类内距离远小于类间距离。     

基于图像纹理特征的目标快速检索

在讨论共生矩阵的基础上,提出了一个通过图像分割获取目标图像纹理特征,进而实现图像快速检索的方法。试验表明,该方法检索目标图像的可靠性较高,具有良好的应用价值。     

Vision-based edge detection between plant column and soil of ningxia lycium barbarum garden

ABSTRACT

The cultivation of Lycium barbarum (L.barbarum) is a highly traditional and advantageous industry in Ningxia, China, and has strong development prospects. At present, the protection, fertilization, picking, and other production aspects of L.barbarum are generally inefficient and labor intensive, presenting a bottleneck that restricts the development of the industry. Developing intelligent production equipment in the form of a ‘general self-moving host platform + operation module’ is an urgent task for the healthy development of the L.barbarum industry. A self-planning, self-organizing, host platform must be able to perform adaptive navigation in complex unstructured environments. For this purpose, a method of edge detection that can distinguish between the plant column and soil is required. Using a color difference model with Otsu’s method for image segmentation, a corrected gradient image based on the marking method is employed to remove small noise regions and then perform edge detection. Experiments demonstrate that one particular color model offers strong adaptability for light and shadow, which is good for distinguishing between the plant column and soil. The proposed method can effectively detect the edges between the plant column and soil, laying the foundation for detecting a suitable path for a self-moving platform and visual navigation.