HSV color model

Applying Research of HSV Color Model and Personality Space to Fashion Shop

HSV颜色模型和个性空间在商品选购中的应用研究

Research and Improvement on Shadow Detection in Expressway Videos Using HSV Color Model

路况视频中HSV彩色不变量阴影检测法研究与改进

By this concept and together with HSV color model , we can successfully segment the face image .

针对这点，本文提出肤色平滑度的概念，并利用这一概念和HSV颜色模型对图像进行分割。

An effective method based on HSV color model for extracting contour lines from color scanned topographical maps was proposed .

提出了一种基于HSV色彩模型的等高线提取方法。

This algorithm is based on HSV color model , which is in accordance with human 's perception and discrimination concerning color .

算法选择符合人的视觉的HSV模型，充分发挥了色度的描述作用。

Based on the HSV color model , the algorithm calculates the distance and the similarity in the color space to segment the color image .

该算法采用基于适合彩色图象相似性比较的HSV颜色模型，首先在颜色空间进行距离和相似度计算；

HSV color model is also used and its color components are analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination conditions .

文中算法采用HSV颜色空间，通过对背景统计模型中各颜色分量的有效分析和区别使用，能够很好地适应不同的环境光照条件。

Subvariable V in HSV color model and the optimal threshold value algorithm were used to process sign area binarization in freeway scene image .

采用HSV颜色模型中的亮度分量和最佳阈值法对场景图像中标志区域进行二值化处理。

According to hue difference between shaded and non-shaded regions , possible shaded regions were extracted by HSV color model at first .

根据阴影与非阴影区域间存在色调差异，利用HSV彩色模型，提取可能阴影区域。

The Feature Vector with different dimension is extracted with this method when extract-ing the color feature of the example image and image in database based on HSV color model .

该方法基于HSV颜色模型提取示例图像的颜色特征与图像库中图像的颜色特征时，提取不同维数的特征向量。

In preprocessing phase , the IC image is segmented using HSV color model and the background noises are removed from the IC noisy image by the morphological operating .

在预处理阶段，利用彩色HSV模型分割原IC图像，然后用形态学开运算消除背景噪音。

Using the H and S weight of the HSV color model , separate the target from the environment with a certain color , by a fast clustering algorithm for two-value image segmentation .

用HSV颜色模型的H和S分量，通过一种基于二值图像分割的快速聚类算法，从环境中分离出具有某种特定颜色的目标物。

The algorithm uses both HSV color model to selectively transform various color components to different grey level and the hopping characteristic of the projection map of plate area to detect license plate precisely .

该算法采用基于HSV颜色模型对不同的颜色分量选择性灰度化和车牌区域投影图跳变特征相结合的方法定位车牌区域的方法。

For detect the scene around the robot , this article provide the technique grounded on color image segmentation and target location : divide the image with HSV color model ; sort the segmentation result with fast image clustering ;

为了对机器人场景进行描述，本文提出了基于颜色的图像分割与目标定位技术：根据彩色图像的颜色特征对图像进行分割，运用快速聚类法对分割结果分类。

A deformed HSV color model conformed to color cluster feature of human 's vision is established . In the space , a suitable cluster algorithm is used to extract main colors , then the original image is converted to main image .

选取能够良好再现人类视觉色彩特征的HSV颜色模型，在此颜色空间内，提取原图像主色调作为颜色特征矢量。

In the study of image segmentation based on color information , through study of shape and color characteristic of road sign , we propose a segmentation method based on HSV color model , this method , the variety of lighting have few effect to color segmentation .

在基于颜色的图像分割的研究中，通过对交通标志色彩特征的研究，提出了不受光照影响的基于HSV模型的交通标志分割方法，H（色度）表示不同的色调；

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 .

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 zoning method the Otsu Dynamic Threshold introduction of shadow , while using the HSV color space model are two ways to be used in conjunction to achieve better results in real-time and effectiveness .

本文将Otsu动态阈值的方法引入阴影的区域划分中，同时使用HSV颜色空间模型两种方法配合使用，在实时性和有效性上取得较好效果。

An improved color structure code ( CSC ) algorithm combining region and edge information in link phase was presented . The difference of color is calculated on hue saturation value ( HSV ) color model .

对色彩结构码（CSC）算法做了改进，将图像边界信息结合进CSC算法的连接过程，并以色度、饱和度、亮度（HSV）色彩模型为基础确定色彩差别。

Start from the existing shadow removal method , in the HSV color space model of the shadow detection methods , the introduction of Otsu dynamic threshold segmentation method used to find the target information area of the shaded area and the movement of vehicles pixel values .

从现有的阴影去除方法入手，在HSV颜色空间模型的阴影检测方法上，引入了Otsu的动态阈值分割方法用于寻找阴影区域与运动车辆目标信息区域像素值。