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该源码演示了如下内容：
1、单独地改变某个控件如静态文本的字体。
2、如何改变控件的背景、前景色-demonstration of the source are as follows : a single change to a certain controls as static text fonts. Two, how to change the control's background, foreground color
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for the TI dm6446 platformBackground subtraction moduleMaintain a background model, which can distinguish background, foreground and theft/left pixelsShadow removal moduleDetect shadow regions in monochrome videosCamera shift detection and suppressio
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使用opencv，将一个视频文件分割成多张图片。
特点：按帧提取，每帧保存为多张图片。
保存时，原来的格式是全彩的，同时转化并保存全彩图片对应的黑白图片和二值化图片。这三类图片分别存放在默认目录的video background foreground中。默认的视频文件名为默认目录下的ci.avi
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混合高斯模型，建立背景模型，从而可以分离前景与背景,Gaussian mixture model, background model, which can be separated from foreground and background
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实现文件的上传下载功能，有一个客户端和一个服务端，利用socket实现后台，前台swing-File upload and download capabilities, a client and a server socket to achieve the background, foreground swing
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基于opencv的背景差法，实现前景和背景的分离。需要先配置好vc2008，然后编译执行。-Opencv background difference based method to achieve the separation of foreground and background. Need to configured vc2008, and then compile the implementation.
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是一个实用的抠图软件，软件很小，对图像的前景和背景分离效果很好-Matting is a practical software, software is very small, the image foreground and background separation worked well
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用Opencv实现的一个运动检测的程序。通过摄像头捕捉，把捕捉到的图像分为前景和背景，从而检测出运动图像。-Achieved with Opencv a motion detection process. Captured by the camera, the captured image are separated into foreground and background, to detect the moving image.
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介绍一种应用于视频运动检测中前景和背景建模分割的方法-proposes a novel method for detection and segmentation
of foreground objects from a video which contains
both stationary and moving background objects and undergoes
both gradual and sudden “once-off” changes.
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程序实现一个自适应阈值的算法，用以在不规则光照下从背景中提取出前景图像。-Procedures to achieve an adaptive threshold algorithm to extract the foreground from the background image in the irregular light.
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the threshold is determined and the foreground and background are seperated
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视频背景非参数估计论文及matlab实现.matlab代码只实现了灰度图的背景估计，论文利介绍的彩色视频处理方法可以自己看看怎么做。-Background and Foreground Modeling Using
Nonparametric Kernel Density Estimation for
Visual Surveillance
AHMED ELGAMMAL, RAMANI DURAISWAMI, MEMBER, IEEE, DAVID HARWOOD, AND
LA
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Determine the background of an image, llowing extract foreground objects
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Image Segmentation (Foreground separated from Background).
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This package contains m-files for the segmentation of a moving foreground from video with a static background
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Demo of the background/foreground detection algorithm
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两次利用大津法对图像进行分割，将前景与背景，白色区与背景分割开，并二值化。-Otsu method twice using image segmentation, the foreground and background, white background area and separate, and binary.
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Tracking w/ blob detection, morphological operation (Togeather)
frames = {avi.cdata} uses the cdata from the video file
fg = extractForeground(frames) do foreground extraction
cmap = colormap(gray)
for i = 1:length(fg)
temp0{i} = edg
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迭代法是基于逼近的思想，逼近的目标是使得：前景和背景的平均灰度值的平均值即为阈值。该方法的原理是：如果用某一阈值分割出的图像，其两部分平均值的中值，正好等于该阈值，那么这个阈值就是所求的阈值。-Iterative method is based on the approximation of the idea of approaching the goal is to make: the foreground and background is the average
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前景提取四种方法，好学易懂，适合初学者！(Foreground extraction)
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