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   hsv color model 8 的翻译结果: 查询用时:0.201秒
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hsv color model
相关语句
  相似匹配句对
     COLOR
     冬季女装色彩预测
短句来源
     Segmentation of vehicle is conducted in HSV color space.
     车辆目标的分割是在HSV彩色空间完成的。
短句来源
     Color Edge Detection Based on HSV Space
     基于HSV空间的彩色边缘检测
短句来源
     The Color of Nature
     大自然的颜色
短句来源
     Transition between color space models of RGB and HSV is implemented.
     实现了RGB到HSV色彩空间模型的转化;
短句来源
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MIROSOT is a complex competition game. Quickly and correctly identifying the position and the movement of the golf ball and robot vehicles is the foundation of making decision and control in winning MIROSOT competitions. In a MIROSOT system, the ball, robot vehicles and background are painted with specified colors, and these different specified colors will serve as indexes for identifying the moving objects. However, the RGB color data of a specified moving object are quite dispersive in different lighting...

MIROSOT is a complex competition game. Quickly and correctly identifying the position and the movement of the golf ball and robot vehicles is the foundation of making decision and control in winning MIROSOT competitions. In a MIROSOT system, the ball, robot vehicles and background are painted with specified colors, and these different specified colors will serve as indexes for identifying the moving objects. However, the RGB color data of a specified moving object are quite dispersive in different lighting circumstances. To solve this problem, a new algorithm for identifying specified color based on parameters H and V with HSV color model is proposed in this paper. This paper also introduces a fast algorithm for identifying the ball and robot vehicles which might be adjacent each other. The running experiments show that the algorithm is reliable and efficient.

机器人足球比赛是一项非常复杂的高技术对抗活动 ,其中快速准确地识别小球和机器人小车是决策及控制的基础 .在足球机器人视觉跟踪中 ,颜色信息是最主要的识别分割依据 ,由于 HSV模型更接近人眼对颜色的感知 ,在不同光照条件下 ,色调参数 H数值较稳定 ,比较适合用做识别处理的基础 .因此使用色调 H和亮度 V作为识别颜色的参数 ,同时为了提高识别速度 ,作了一些改进 ,并提出一种橙色高尔夫球和机器人小车的快速识别算法 .试验快速准确 ,证明了该算法的可靠性和有效性 .

Based on the divided computing nets in computational fluid dynamic(CFD) and by using the continued color shading algorithms, the paper identifies the steps involved in the scientific visualization and animation of CFD results in 2D scalar data fields. The methods of the triangle element division from general rectangle elements and the shading algorithm combined with Gouraud\|Shading and barycentric interpolation are described in detail in this paper. According to the characteristics and properties of...

Based on the divided computing nets in computational fluid dynamic(CFD) and by using the continued color shading algorithms, the paper identifies the steps involved in the scientific visualization and animation of CFD results in 2D scalar data fields. The methods of the triangle element division from general rectangle elements and the shading algorithm combined with Gouraud\|Shading and barycentric interpolation are described in detail in this paper. According to the characteristics and properties of HSV color model in the computer graphics, the two different kinds of linear interpolations between scalar data and used color value are used to visualize the CFD results in the form of static state and dynamic state. As an example, the procedure to simulate the changes of fluid function and turbulence strength values resulting from CFD for a wing section is presented to demonstrate that the proposed methods are viable.

针对某翼型设计的 CFD计算结果 ,采用色调连续变化的图像映射方法 ,基于划分的计算网格 ,提出了三角单元结构的抽取和将 Gouraud-Shading与质心坐标插值法相结合的扫描线转换算法 ,并根据 HSV颜色模型的特点建立了可视化标量与颜色值之间的两种线性对应关系 ,在此基础上实现了翼型设计的 CFD计算结果中流体流函数和旋涡强度二维标量场的静态和动态可视化显示 ,实例证明了算法的有效性

Extracting the extra materia defect features from an IC real image is very important to the classification and recognition of the defect in the IC real manufacturing process. In this paper, a boundary detecting method based on mathematical morphology for IC real extra material defects is presented at first. Secondly, the boundary chain code of the extra material defect is generated from the IC boundary image. Finally, several size and shape features are detected so that the IC extra material defect can be identified....

Extracting the extra materia defect features from an IC real image is very important to the classification and recognition of the defect in the IC real manufacturing process. In this paper, a boundary detecting method based on mathematical morphology for IC real extra material defects is presented at first. Secondly, the boundary chain code of the extra material defect is generated from the IC boundary image. Finally, several size and shape features are detected so that the IC extra material defect can be identified. 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. This step is followed by morphological eroding and dilating for filling holes in the segmented IC image obtain the isolation and extraction of IC extra material defects from a complex scene. Once isolated, the extra material defect boundary can be examined by using morphology operators. The group size features (those are area, perimeter, object core, width and length) and the shape feature (those are called rectangularity and circularity measures) are detected from the boundary image. Experimental result shows that proposed methods make the shape analyzing of IC extra material defects simple and detectable.

为了对 IC制造中真实多余物缺陷进行分类与识别 ,IC多余物缺陷的特征提取是非常重要的一步 .文中首先提出一种基于数学形态学的 IC真实多余物缺陷边界的检测方法 .其次对边界进行了链码描述 .最后对边界所表示的多余物缺陷进行了尺寸测量与形状分析 .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 .对开后的结果图像进行形态膨胀及形态腐蚀运算 ,消除多余物缺陷中的小洞噪音以获得从复杂背景中分离和抽取多余物缺陷 .对分离后的缺陷用形态学算子提取边界 .由缺陷边界检测出一组缺陷的尺寸特征 (面积、周长、形心、宽度、高度 )及缺陷的形状特征 (矩形度、圆形度特征 ) .实验结果表明该文方法使多余物缺陷形状分析简单且易于测量 .

 
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