背景图像

COLD文档是一种特殊类型的文档，包含叠加在背景图像上的文本。

A COLD document is a special type of document that has text superimposed on a background image .

完成了复杂背景图像中单个细胞的检出，形态特征的提取，BP分类器的设计。

The detection of single cell , extracting of morphological features in complex background image and design of BP sorter are finished .

教程步骤一步使用CSS来创建背景图像列表，滚动列表，列表的嵌套列表和水平。

Step by step tutorials on using CSS to create background image lists , rollover lists , nested lists and horizontal lists .

这包括用于视频每个帧的背景图像和文本ELENA的前景图像。

This includes the background images for each frame of the video and the foreground image of the text ELENA .

对背景图像进行非失真压缩，而对变化图像运用EZW算法进行编码。

The method processes the background image with lossless compressing , while changing image with EZW algorithm .

简而言之，使用带有实际文本的div会更加简单和准确，然后可以为div添加一个背景图像。

In short , it 's simpler and more accurate to use divs with actual text , and then drop in a background image for the div.

最后，针对超声背景图像，在现有EMD压缩编码方法基础上，提出了考虑局部极点分布位置的非均匀变采样的EMD压缩模式，具有一定的创新意义。

Last , the paper introduces EMD compression mode using non-uniform variable samplings considering the local extrema distribution based on the existing coding method of EMD and has made some innovation .

最后需要注意的一点：相对于在XHTML中实际放置一个img标记而言，您可能更喜欢在div中使用背景图像。

One last word of caution : You should favor using a background image in a div over actually placing an img tag in your XHTML .

根据彩色差值模型计算当前帧图像和当前逼近背景图像的差分图像；并引入Gauss模型实现了运动目标的自适应阈值分割。

Moreover , the difference image is obtained by using a color image difference model , and then a self-adaptive thresholding segmentation method for moving objects detection based on Gauss model is developed and implemented .

记住要采用与分配PNG文件作为OneView背景图像的相同方式使用Identity窗口将正确的值分配给静态标签。

Remember to assign the correct value to the static label using Identity windows in the same manner as you assigned the PNG file for the backgroung image of OneView .

算法直接在RGB空间或灰度空间进行，无需进行颜色空间转换，也无需建立单独的背景图像，计算量小，处理实时性高。

The algorithm can be directly used on RGB space or grey space , without changing color space or building the background model , it is computationally simple to implement and has high real-time processing performance .

阐述了图像采集系统的工作原理，以及CPLD芯片、双口RAM存储器的具体操作方式.介绍了运用浮动阈值算法进行图像相关，进而从背景图像中识别出小目标的软件算法。

The principle of the system and the operating method of CPLD , double ports RAM chip are introduced , and the software algorithm of recognizing a small target from background image by applying floating threshold value between correlative images is presented .

讨论了Hausdorff距离的性质以及计算方法，指出了在复杂的背景图像中，利用有向Hausdorff距离进行图形符号匹配的适用性，并且提出了一个计算Voronoi曲面的具体算法。

The property and computing method of Hausdorff distance is discussed . The using of directed Hausdorff distance to match graphics in clutter background is verified . An algorithm is used to compute the Voronoi surface .

通过学习已有研究成果，针对背景图像提取速度慢、准确度低的问题，提出一种RGB空间像素点变化统计和中值法相结合的背景建模法。

Through the study of existing research results , in view of the low speed and accuracy in background image extraction , propose a method of building background model by combining RGB space pixel change statistics with median algorithm .

在SSRS的报表设计器中，我们在所有需要显示数据库中信息的位置上添加文本框和复选标签，并根据其背景图像上的线条来设定它们的位置。

In SSRS Report Designer , we add all the textboxes and checkmarks where the information from our database will be shown , and position them according to the lines of the background image .

这样，我们只有当页面是在屏幕上显示时使用低分辨率的背景图像和并在打印时隐藏它（根据ForPrint参数值进行判断）。

This way we show the low resolution background image of this page during screen viewing and hide it during printing ( based on the value of ForPrint parameter ) .

在NAS-RIF算法中，提出了支撑域的改进算法和对非均匀背景图像的校正方法，提高了图像的复原质量，同时对图像梯度算法进行了改进，提高了算法的执行效率。

In NAS-RIF , propose the improvement algorithms of supporting and correcting the nonuniform background image , besides , the modified gradient algorithm is described . All of these will improve the efficiency of image restoration .

然后将这些矢量纹理作为IBFV算法中的背景图像，代替原来的噪声纹理与帧缓存中的纹理进行图像混合生成新图。

Then the vector textures are performed image blending with texture of frame-buffer to generate rendering images , which are treated as the background images of IBFV algorithm instead of noise textures .

本文针对复杂背景图像中文字与背景区域的形态特征，提出了一种基于形态运算和区域生长的快速文字分割算法MOSA，同时将之与LLT分割算法进行了比较。

According to the morphic characteristics of the Chinese characters and background areas in a complex background image , we propose a fast text segmentation algorithm based on morph operation , and compare it with the LLT algorithm .

实验结果表明，该算法能较快和较准确地定位复杂背景图像中的文字区域，并且相对于LLT算法，该算法在速度与分割效果方面都有所提高。

The experimental results show that our algorithm can locate the text in a complex image in a very fast and precise way . In comparison with LLT , our algorithm has a higher processing speed and better segmentation result .

其次，利用原始图像减去背景图像得到差图像，以消除不均匀背景对图像分割的影响；

Second , the original image is subtracted by the background ;

基于自适应背景图像更新的运动目标检测方法

A Moving Object Detection Method Based on Self-Adaptive Updating of Background

基于C-均值聚类的视觉监控背景图像构建算法

A Background Reconstruction Algorithm Based on C-means Clustering for Video Surveillance

您可以生成您自己的按钮背景图像文件。

You can generate your own image files for button backgrounds .

云杂波背景图像序列中小目标检测算法研究

Detection Algorithm for Small Target in Cluttered Cloud Background Image Sequences

首先，利用形态学方法估计出导引头红外图像中的背景图像；

First , the background is estimated by morphological operations ;

复杂背景图像中的叠加文字提取技术研究

Research on Overlay Text Extraction from Images with Complex Background

例如，您需要在这个阶段处理所有背景图像。

For example , you handle all background graphics during this phase .

背景图像如何附加到文档中的元素

How the background image is attached to an element within the document

拖到绘图页后，可以添加整页大小的背景图像。

Drag onto the page to add a full-page sized background image .