颜色直方图

基于分块颜色直方图的MeanShift跟踪算法

Tracking Algorithm Based on Block Color Histogram and Mean Shift

本文利用VISUALBASIC6.0程序设计语言实现了在Windows2000环境下基于颜色直方图算法的多媒体图像数据库检索系统。

In the Windows 2000 environment , the image retrieval demo system , which was based on the image color histogram characteristic , was implemented with Visual Basic 6.0 programming language .

基于HSV分块颜色直方图的图像检索算法

An image retrieval algorithm based on HSV color segment histograms

实验结果表明，权重参数的选择与图像的颜色直方图、Hu形状不变矩之间存在着一定的联系。

Experimental results show that there are some contacts between weighting parameters and the features of color histogram and Hu moment invariants .

实验结果表明，集成的图像特征表示在图像分类实验中取得了很好的效果，具有比其他特征表示（如Gabor纹理、颜色直方图）更好的性能。

Experiment results show that the combination descriptor is more discriminative than other feature descriptors such as Gabor texture .

对于目标跟踪，则采用了MeanShift与卡尔曼滤波相结合的方案，有效地利用了目标的颜色直方图信息与目标的运动状态信息，可以准确地实现跟踪。

The combination of Mean Shift and Kalman Filter is adopted for object track , utilizing the information of both color histogram and motion state of the object , which help to guarantee the precision .

在此基础上，集成纹理、边缘和颜色直方图作为图像的特征向量，用支持向量机（SVM）实现图像的语义分类。

Furthermore , with the incorporation of the color , texture and edge histograms seamlessly , the images are grouped into semantic classes using a support vector machine ( SVM ) .

第一，提出了一种基于统计Gabor小波特征和颜色直方图的国画分类算法。

The main contributions are as follows : Firstly , we propose an automatic classification algorithm of traditional Chinese painting based on statistical Gabor feature and color feature .

其中包括：压缩视频DC图象的获得、DC图象的HSV颜色直方图表示、直方图实现镜头边缘检测、直方图实现镜头代表帧抽取以及代表帧的特征提取等。

It includes obtaining DC image of compressed video , expressing HSV color histogram of DC image , using histogram to detect shot , extracting represent frame from shot and feature extracting of represent frame .

该算法利用RGB空间中的颜色直方图分布得到阈值，再对图像进行滤波后进行边缘检测和直线拟合。

The threshold is obtained from the histogram of RGB space to filter the irrelevant color . Then the raceway is recognized using edge detection and line fitting .

用高斯核函数正规化目标区域，进而加权计算目标的HSV颜色直方图，将该直方图作为粒子滤波器的目标模型进行跟踪。

First , regularize the target region with Gaussian kernel . Second , calculate its HSV color histogram which is to be used as the target model of a particle filter .

提出了一种基于显著点的颜色直方图图像检索新方法，克服了基于显著点Hu不变矩图像检索方法没有考虑颜色信息的弊端。

A new method for image retrieval based on color histogram of salient points is proposed , which eliminates negative influence of Hu invariant moment image retrieval method based on salient points without considering color information .

采用多重交叉检验的ROC评估，实验表明结合颜色直方图和颜色边缘直方图能明显提高分类精度；

Using ROC evaluation in multi_fold cross validation , experiments shows that the classification accuracy can be significantly improved when the color histogram is combined with the color edge histograms .

该算法采用HSV空间中的H分量的颜色直方图作为目标模型，并用几何矩来提取图像特征，在监视目标旋转、遮挡以及监视环境亮度改变时，也具有较好的鲁棒性。

The algorithm takes the color histogram of H component in HSV space as a target model , and extracts geometric moments as image features , it reveals strong robustness in the case of target rotated , occluded and lightness changing .

本文提出并实现了一套完整的行人跟踪系统，整个系统的底层是由HOG特征和颜色直方图特征构成的行人检测器，上层则采用粒子滤波器算法，结合各个行人检测器的结果得到最终检测结果。

In this article , we proposed and implemented a human tracking system whose bottom layer is human detectors based HOG feature and color histogram feature , and upper layer is based on particle filter .

对粒子滤波方法进行了深入研究并应用于海面船只跟踪系统中，通过HSV颜色直方图和形状特征相融合的方法，提高了跟踪系统的准确性和鲁棒性。

We explore the particle filtering method and put it into the ship tracking system . We improve the accuracy and robustness of the tracking system through the combination of HSV color histogram with shape features .

在对HSV彩色模型做特殊处理的基础上，采用整数小波变换低频部分的量化颜色直方图代表颜色特征，小波多尺度表示方法中细节信息的方差统计量代表纹理特征。

Based on the special disposal on the HSV color space , the color histogram taken from low frequency band is used as color feature , the statistics information of high frequency band is used as texture feature .

Corel图像库中每幅图片分别通过颜色直方图，颜色一致向量，PWT和Hu矩提取得到4个特征文件，作为图像识别实验系统的输入数据。

Four datasets are retrieved from Corel image database by color histogram , color coherence vector , PWT and Hu moments respectively , which input the image recognition experimental system .

首先，提取出彩色图像的重要位平面，然后在位平面的基础上用Harris算子提取出图像的感兴趣点，最后对这些感兴趣点进行模糊颜色直方图的计算，进行图像检索。

Firstly , the significant bit-planes are extracted from the color image . Then , the Harris-Laplace detector is utilized to extracted interest points from the significant bit-planes . Finally , calculate the fuzzy color histogram based on salient points .

在对三维传统的颜色直方图（CCH）作出了一系列改进的基础上，提出了一种基于主色外观图（DCG）的新的彩色图像分割方法。

This paper proposed a color image segmentation algorithm based on dominant color graph ( DCG ) on the basis of the improvement of tri-dimensional conventional color histogram ( CCH ) .

在预分割过程中，采用基于Lab三维颜色直方图的分水岭算法对颜色空间进行聚类，然后利用基于最高置信度优先算法的马尔可夫随机场模型得到最终的结果，从而避免过高的计算复杂度。

In the first step , the watershed algorithm is applied on 3-D Lab color histogram . The Highest Confidence First ( HCF ) algorithm for Markov random fields is taken as the second step to refine the raw result to get continuous regions with relatively low computational load .

然后在检索匹配时，用各尺度的标准差和偏斜度进行递进筛选，再用LL子带的HSV颜色直方图计算图像之间的相似性距离，进一步对检索结果求精。

When matched retrieval is conducted , progressive filtration is processed by using multi-scale moment , and then HSV bar graph of the LL sub-band is used to calculate the similarity distance between the images for further refining the retrieval result .

将目标的加权颜色直方图作为目标的颜色模型，并利用Bhattacharyya距离描述粒子与目标颜色模型的相似性，为粒子权值更新提供有力依据。

This thesis presents the integration of weighted color histogram into particle filter , which takes into account the target 's shape as a necessary factor in target model .

台标粗识别阶段主要利用HSV空间得到的一维颜色直方图特征矢量确定候选台标模板集；台标精确识别阶段主要是利用归一化互相关匹配识别来实现。

In the coarse recognition stage , the one-dimensional color histogram feature vector obtained by HSV space is used to determine the set of logo candidates . In the fine recognition stage , the normalized cross-correlation is used to achieve matching and recognition .

此跟踪算法利用HSV彩色模型中的色度分量H来计算人脸区域的颜色直方图，同时为了剔除与人脸区域色度信息相近的区域，加入了饱和度信息和亮度信息。

The component H of the HSV color model is used to calculate the color histogram of the face region , at the same time , in order to remove the area close to the hue information of the face region , the information of saturation and value are added .

针对同一图像库的检索试验表明，与本文所提出的第一种方法比较，查准率提高5.5%，与全局HSV颜色直方图相比较，查准率提高2.5%。

The experimental result of the same images database demonstrates its retrieval precision is increased 5.5 % comparing with the first method be proposed in this dissertation , and it can increase the retrieval precision 2.5 % , comparing with global HSV color histogram image retrieval method .

在系统中采用了72柄颜色直方图和形状不变矩作为区域特征表示，采用IRM方法计算两幅图像的综合区域相似度，并改进了IRM算法中区域重要性因子的度量方法。

In the prototype system , 72 bin color histogram and moment were chosen as region feature , and we use the IRM measure to calculate the distance between two images . A method is proposed to adjust region importance in IRM .

该算法首先将视频分割为镜头，并提取镜头的关键帧，然后计算关键帧的颜色直方图和MPEG-7边缘直方图，以形成关键帧的特征；

At first , the video clips are segmented into shots and the shot key frames are extracted . Then the features of color histogram and MPEG-7 edge histogram of each key frame are computed and the feature vectors of shot key frames are formed .

使用尺度不变特征描述器描述的Harris-Laplace兴趣点以及边缘颜色直方图描述的边缘特征表示图像。

The content of an image is characterized by two kinds of features : Harris-Laplace interest points described by the scale invariant feature transform ( SIFT ) descriptor and edges described by the edge color histogram .

本文将多尺度图像的信息量度量方法引入到运动目标跟踪中，提出了一种跟踪窗口自动更新算法，并用此算法改进了基于颜色直方图的Mean-Shift跟踪方案。

The information measure of multi-scale image in scale space has been used to differentiate the scale and is introduced into moving object tracking in this paper . Automatic updating method of tracking window is proposed , and is integrated into the classical Mean-Shift tracking algorithm based on color histogram .