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背景相減法&連通域標記來實現目標偵測
包含去陰影、形態學運算、框出目標物-Background subtraction & connected component labeling to achieve the target detection
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1. 用ＤＦＳ判断一个无向图是否是连通图；
2. 为有向图的边分类，将它们的边分为前向边、后向边和交叉边；
3. 用ＤＦＳ和点消除求有向图的拓扑排序；
4. 判断有向图是不是强连通图，若不是，求强连通分量；
5. 判断有向图是不是半连同图；
6. 判断有向图是不是单连通图；
7. 判断无向图是不是双连通图。
通过以上编程对ＤＦＳ的应用，进一步了解ＤＦＳ的算法及它所代表的算法思想。
-1. Using DFS to test if a given undirecte
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该算法为领域标记程序，可以检测 blob 区域-the algorithm for field marking procedures can detect regional blob
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nvidia CUDA 2.0 SDK
中文版本,翻译率大概为95％-nvidia CUDA 2.0 SDK Chinese version, the translation rate of about 95
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寻找图像物体的外轮廓，通过Connected component分析实现-Find images of objects outside the contour, through the Connected component analysis to achieve
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This program calculates the number of connected components in a graph (Two vertices are in the same connected component of the graph, if there exists a path between these two vertices.
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强连通分量的实现 强连通分量的实现 -Strongly connected component strongly connected component to achieve the realization of strongly connected components to achieve the realization of strongly connected components
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python code to do connected component labeling of the thresholded image
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A rough implementation of "A Component-Labeling Algorithm Using Contour Tracing Technique" paper on an implementation of connected component algorithm using contour tracing, allowing the algorithm to do connected component labelling with just one pas
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this useful program for identifying blobs in video stream . called connected component labeling Algo. -this is useful program for identifying blobs in video stream . called connected component labeling Algo.
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this is very simple connected component algo. we can easily understand this algo as well .
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本程序应用了取两次阈值、基于特征的逻辑、二值形态学和相连成分的标识，确定了钢的显微图像中颗粒的边界，标识了不同的颗粒。-This procedure applies to take the two threshold values, based on characteristics of logic, binary morphology and connected component labeling, to determine the microstructure of steel grain
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一种多车牌定位方法，该方法综合利用边缘检
测、连通域分析、倾斜矫正等多种方法,解决了复杂背景中定位难的问题-A multi-plate location method, which combined with an edge detection, connected component analysis, tilt correction and other methods to solve the complex problem of difficulties in the context
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这个函数获取二进制图像，然后根据图像中标记目标的连接性和每个连接组成的像素数量来判断是否是噪声。 -The function to get the binary image, then image tag target connectivity and the number of pixels of each connected component to determine whether it is noise.
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Connected component labeling by an Iterative algorithm used for labeling image pixel.It will divide the region according to pixel value.
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This contained BG/FG detection(simple version and adaptive background mixture models), blob tracking(connected component tracking and MSPF resolver, mean shift, particle filter), Kalman filter using OpenCV. It can be helpful who studying object detec
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这是一个使用vc++实现的图像连通区域标记算法，可以找出二值化图像的连通域个数。-This is achieved using vc++ image connected component labeling algorithm can find the binary image of the number of connected domains.
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将图像中的连通域部分分别提取出来，但是输出的时候不能连续输出，我用的是最繁琐的方法-The the connected domain part of the image were extracted, but the output is not continuous output, I used the most tedious method
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图的强连通部分,给定一个有向图，求改图的强连通部分-the strongly connected component
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The basic steps of the connected-component text extraction algorithm are given below,
and diagrammed in Figure 10. The details are discussed in the following sections.
1. Convert the input image to YUV color space. The luminance(Y) value is used
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