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Connected Component Labeling,Connected Component Labeling
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用VC++实现图像连通区域标记-Image using VC++ to achieve connected component labeling
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图像连通域标记c语言程序,在VC++环境下可执行，连通域分析是在图像处理中常用的分析方法，希望本代码可以帮助到需要的人。-Image connected component labeling c language program
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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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Strongly Connected Component Library to obtaion strongly connected components of a graph, for PC platforms writeen in Visual C-Strongly Connected Component Library to obtaion strongly connected components of a graph, for PC platforms writeen in Visua
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java实现图像连通区域算法
*ImageLabel is an algorithm that applies Connected Component Labeling
*alogrithm to an input image. Only mono images are catered for.-*ImageLabel is an algorithm that applies Connected Component Labeling
*alogrithm to an input
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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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connected component using OpenCV
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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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数字图像处理利用形态学进行连通分量提取法程序-Digital image processing using morphological connected component extraction process
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实现形态学的阈值分割，可得到分割后的阈值图像，形态学图像，L的直方图，最大连通成分提取图像以及最后得出的结果图像。-Achieve morphological thresholding, the threshold obtained after image segmentation, image morphology, L histogram, the largest connected component extraction result image and the final image.
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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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对于数字图像连通区域标记的一种方法，简便快捷-A method of digital image connected component labeling, quick and easy
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提取一幅图像中的最大连通分量，即物体的最大外边缘-extract connected component
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这里包括2015年论文利用游程集合的标号传播实现快速连通域标记的论文原文和源代码，有作者本人提供，检测二值图像的连通域，我们认为速度比其他算法快得多。-Fast Connected component labeling
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Connected-component labeling (alternatively connected-component analysis, blob extraction, region labeling, blob discovery, or region extraction) is an algorithmic application of graph theory, where subsets of connected components are uniquely labele
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