一种新的基于加权颜色特征的图像检索算法

针对传统基于颜色直方图为特征的图像检索算法的不足,提出了一种新的颜色特征提取算法.利用模糊C均值聚类(FCM)对HSV空间的颜色信息进行聚类,然后对颜色信息进行加权颜色直方图统计,得到主颜色直方图.实验结果表明,新的加权主颜色直方图的图像检索算法比传统颜色直方图具有更高的检索精度.     

基于颜色的自组织聚类分析图象检索算法

本文提出了一种改进的迭代自组织聚类分析方法（ISODATA）来实现基于颜色的图象检索。算法选择符合的人的视觉的HSV模型，充分发挥了色度的描述作用。同时，选择HSV空间上的颜色直方图作为颜色特征，该特征描述了图像颜色的统计分布特征，且具有平移，尺度和旋转不变性，算法改进了ISODATA的初始聚类中心的选取方法，其初始聚类中心的选择是面向数据分布的，具有较好的通用性，因此适合各种分布特性的数据对象，实验结果表明，算法的检索精度明显好于传统的基于RGB直方图的检索结果。     

CLAHE算法在不同彩色空间中的图像增强效果评估

直方图均衡是一种常用的灰度图像增强算法,很多研究者对其做了各种改进,但少有人研究其在不同颜色空间上的增强效果.研究了对比度限制的自适应直方图均衡(CLAHE)图像增强算法,并介绍了图像和视频处理中常用的RGB、HSV、YIQ、YCbCr和Lab 5种颜色空间,给出了均方误差(MSE)、峰值信噪比(PSNR)、彩色增强因子(CEF)和结构相似度(SSIM)4个图像质量评价指标的计算公式,并用这4个指标评价了CLAHE算法在5种颜色空间上的增强效果.实验结果表明,相比于其它4种颜色空间,CLAHE算法在HSV颜色空间上取得了最好的增强效果.     

基于颜色和空间特征的图像检索

在环形颜色空间划分和颜色视觉关注度的基础上,提出一种新的基于颜色和空间分布特征检索算法.首先,在HSV色彩空间下进行颜色量化并计算每种颜色的质心,进行环形颜色空间分割.然后计算各环形颜色空间直方图,在此基础上计算图像的空间颜色分布矩.同时计算各种颜色对应像素的平均视觉关注度,以此作为该颜色特征的视觉关注特征.最后对特征向量进行高斯归一化,采用特征向量的L1-norm距离计算彩色图像的相似度并进行图像检索.实验结果表明,本文算法比SCH及Geostat方法具有更好的检索效果.     

一种基于HSV空间和粗糙集的彩色图像分割方法

研究了基于HSV颜色空间的粗糙集直方图阈值彩色图像分割方法.根据HSV空间的特性,定义了HSV空间颜色距离计算公式,对HSV三分量计算粗糙集直方图和彩色图像进行分割.实验结果表明该方法较好地保留了图像的颜色信息,具有较高的通用性,能够获得满意的分割效果.     

基于色彩量化及索引的图像检索

提出了一种基于色彩量化及索引的图像检索新方法.结合人眼视觉感知特性,首先将图像划分成4×4大小的非重叠子块,通过块梯度的大小,在亮度空间将图像子块划分为视觉均衡块和非均衡块.若为均衡块,则用该块RGB空间的颜色均值作为其代表颜色值,然后转换到HSV空间,并量化成32个等级,形成32维索引直方图(S_HIST);若非均衡块,根据保持颜色矩不变技术将该图像子块在RGB空间量化两种颜色,然后转化到HSV空间,并将每种颜色量化成32个等级,形成496维的索引直方图(D_HIST).最后,综合索引特征,进行图像检索.实验结果表明:该算法是非常有效的.     

十种基于颜色特征图像检索算法的比较和分析

在基于内容的图像检索中,颜色特征已得到广泛应用.本文对十种利用颜色特征进行图像检索的算法利用同一图像库进行了实验比较.实验结果表明,无论在HSI空间或MTM空间,累加直方图法均优于一般直方图法,对这一点本文还首次给出了严格的理论证明.实验结果还表明,加权距离法比欧氏距离法总体上没有明显改善,MTM空间比HSI空间也没有显出优势,而中心矩法算法简单,检索速度快,通过调整加权系数,检索精度可以接近累加直方图法.本文的实验和分析对选择和优化检索算法有一定的参考价值.     

基于分块颜色直方图和GWLBP的图像检索算法

为了提高多特征融合图像检索的效果,本文提出了一种基于分块颜色直方图和GWLBP的图像检索算法。算法采用K-means均值聚类对RGB颜色空间进行颜色聚类,再将4×4均匀分块图像分成9个子块,提取每个子块的颜色体积直方图,并赋予不同权值计算颜色特征;利用Gabor滤波器组对输入图像进行不同分辨率和方向滤波,然后将不同方向上局部滤波器输出结果与全局滤波器输出结果的平均值进行比较,并进行二值化,据此提出3种不同的GWLBP算子来提取纹理特征。最后对图像的颜色和纹理特征高斯归一化,采用加权平均来融合颜色和纹理的特征距离。通过实验仿真可知,与其他3种算法相比,本算法对正常和有旋转倾向的图像都有较高的查全率和查准率。     

应用颜色信息的图像分割研究

提出了一种在RGB颜色空间中颜色距离定义的方式,并根据颜色距离,用Roberts梯度算子得到颜色距离直方图,确定图像边缘信息的阈值。通过Roberts算子,使用此阈值得到图像的边缘信息。这种方式,充分考虑了图像中的颜色信息,与灰度图的处理方式相比,减少了计算量,提高了具有相似亮度的不同颜色之间边缘信息的提取成功率。     

量化颜色直方图的改进与应用

对图像进行灰度量化时,容易把颜色不同而灰度相同的像素归为一类,造成量化误差而影响评价结果。基于HSV颜色空间,通过统计样本数据,结合人眼观察彩色的视觉特性,确定了颜色量化范围,建立了适合伪装特点的颜色直方图,利用距离函数进行了目标颜色特征的伪装效果评价。实验结果表明,利用改进的量化颜色直方图评价目标伪装效果,能够客观地...     

An image retrieval method based on spatial distribution of color

Color histogram is now widely used in image retrieval. Color histogram-based image retrieval methods are simple and efficient but without considering the spatial distribution information of the color. To overcome the shortcoming of conventional color histogram-based image retrieval methods, an image retrieval method based on Radon Transform （RT） is proposed. In order to reduce the computational complexity, wavelet decomposition is used to compress image data. Firstly, images are decomposed by Mallat algorithm. The low-frequency components are then projected by RT to generate the spatial color feature. Finally the moment feature matrices which are saved along with original images are obtained. Experimental results show that the RT based retrieval is more accurate and efficient than traditional color histogram-based method in case that there are obvious objects in images. Further more, RT based retrieval runs significantly faster than the traditional color histogram methods.     

A fast and efficient color image enhancement method based on fuzzy-logic and histogram

A new fuzzy logic and histogram based algorithm for enhancing low contrast color images has been proposed here. The method is computationally fast compared to conventional and other advanced enhancement techniques. It is based on two important parameters M and K, where M is the average intensity value of the image, calculated from the histogram and K is the contrast intensification parameter. The given RGB image is converted into HSV color space to preserve the chromatic information contained in the original image. To enhance the image, only the V component is stretched under the control of the parameters M and K. The proposed method has been compared with conventional contrast enhancement techniques as well as with advanced algorithms. All the above techniques were based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The performance of the different contrast enhancement algorithms are evaluated based on the visual quality, Tenengrad, CII and the computational time. The inter comparison of different techniques was carried out on different low contrast color images. Based on the performance analysis, we advocate that our proposed Fuzzy Logic method is well suited for contrast enhancement of low contrast color images.     

An Efficient Particle Filter–based Tracking Method Using Graphics Processing Unit (GPU)

Particle filter has been proven very robust in handling non-linear and non-Gaussian problems and has been widely used in the area of object tracking. One of the main problems in particle filter-based object tracking is, however, its high computational cost induced by the most time-consuming stage of measurement model computation. This paper makes progress in resolving the problem by proposing an efficient particle filter-based tracking algorithm using color information. First, a compact color cooccurrence histogram is presented, which considers both spatial and color information and can effectively represent color distribution with a very small number of histogram bins. The paper also introduces integral images by which the cooccurrence histogram can be obtained with simple array reference operations. However, the construction of the integral images on the CPU may be computationally expensive. Hence, this paper develops parallel algorithms on a desktop Graphics Processing Unit (GPU), which accomplishes the integral images construction and cooccurrence histogram computation after bin index determination. The resulting algorithm is quite efficient and has better performance than the traditional histogram-based tracking algorithm. The tracking time of the proposed algorithm increases insignificantly with the growth of particle number, and it remains consistent among varying image sequences and stable throughout all frames in the same image sequence due to its irrelevance to object size. Experiments in diverse image sequences validate our conclusions.     

Image retrieval using both color and texture features

In order to improve the retrieval performance of images, this paper proposes an efficient approach for extracting and retrieving color images. The block diagram of our proposed approach to content-based image retrieval (CBIR) is given firstly, and then we introduce three image feature extracting arithmetic including color histogram, edge histogram and edge direction histogram, the histogram Euclidean distance, cosine distance and histogram intersection are used to measure the image level similarity. On the basis of using color and texture features separately, a new method for image retrieval using combined features is proposed. With the test for an image database including 766 general-purpose images and comparison and analysis of performance evaluation for features and similarity measures, our proposed retrieval approach demonstrates a promising performance. Experiment shows that combined features are superior to every single one of the three features in retrieval.     

基于嵌入式零树小波编码直方图图像检索

图像和视频应用的快速增长，使得根据图像和视频内容进行查询的技术变得越来越重要，人们提出了许多基于像素域或压缩域的图像检索技术，因为多媒体数据库通常具有相当大的数据量，所以基于像素域图像检索技术的计算复杂度相当大，因此，许多文献提出更快的基于压缩域的图像检索技术，本文提出一种改进的基于嵌入式零树小波编码直方图的图像检索技术，特征提取综合考虑图像的颜色，纹理，频率和空间信息，所有的特征可以在压缩过程中自动得到，图像检索的过程就是匹配待检索图像和来自数据库的侯选图像的索引，实验证明这种方法具有好的检索性能。     

一种改进的颜色匹配对图像检索算法

以子块直方图彩色图像检索算法为基础， 分析了进一步利用图像空间相似信息的颜色匹配对检索算法的性能。在子块直方图的构成、直方图距离值的归类等方面提出了行之有效的改进方法；给出了子块大小、相似度阈值等参数选择的优化原则，使查准率、查全率等检索性能指标得到了较大的提高，得出了几个有用的结论并形成了实验系统。