Description: 以rice．tif为图像实例，介绍用形态学方法对灰度图像进行处理与分析的技术要点，即对灰度图像进
行如下操作：去除图像的不均匀背景；用设置阈值的方法(thresholding)将结果图像转换成二值图像；通过成分标记(components labeling)返回图像中的目标对象属性，并计算目标对象的统计数字特征。-to rice. Tif images for example, introduces the morphology of gray image processing and analysis techniques, that the gray image proceed as follows : Removal of uneven background image; by setting the threshold value method (thresholding) will be converted into images results binary image; through the composition tags (components labeling) to image targets attribute, and calculate the statistics target characteristics. Platform: |
Size: 1784 |
Author:何子鸣 |
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Description: 以rice．tif为图像实例，介绍用形态学方法对灰度图像进行处理与分析的技术要点，即对灰度图像进
行如下操作：去除图像的不均匀背景；用设置阈值的方法(thresholding)将结果图像转换成二值图像；通过成分标记(components labeling)返回图像中的目标对象属性，并计算目标对象的统计数字特征。-to rice. Tif images for example, introduces the morphology of gray image processing and analysis techniques, that the gray image proceed as follows : Removal of uneven background image; by setting the threshold value method (thresholding) will be converted into images results binary image; through the composition tags (components labeling) to image targets attribute, and calculate the statistics target characteristics. Platform: |
Size: 1024 |
Author:何子鸣 |
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Description: 对二值图像联通区域进行标记，采用一次遍历模式，方便快捷。-Binary image of the region Unicom marks, the use of an ergodic model, convenient and quick. Platform: |
Size: 1024 |
Author:RL |
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Description: 八值图像连通区域标记，为每个连通区域分配一个唯一的标号，处理后的图像按照从左到右，从上到下的顺序获得连续的标号-Binary image connected region eight marks, for each connected region a unique label distribution deal with in accordance with the image from left to right, from top to bottom order of access to continuous labeling Platform: |
Size: 2048 |
Author:zhangjing |
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Description: 基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理。-Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing. Platform: |
Size: 1024 |
Author:mayan |
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Description: 基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 -Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing Platform: |
Size: 1024 |
Author:秦陈刚 |
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Description: Implementation Of Labeling Connected Components
用C#实现图像的连通区域标定，可选4连通，8连通-Implementation Of Labeling Connected Components
The algorithm is coded in C# using unsafe so the quality and speed of the program may not be affected. The class BitmapData is used to read and process the pixels in the image. This is the specialty of C# to provide such a speed even on image processing applications. There is a set of modules that are designed to implement the algorithm. The program scans the image to convert the image into grayscale Levels. Then it converts the image into binary. This binary image will be subjected to splitting it into components. Here we can us 4-Connected or 8-Connected Algorithm but we used 8-Connected Algorithm for finding the Blobs in the image as described above Platform: |
Size: 53248 |
Author:程磊 |
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Description: it is a image processing project which can find special and certain object with certain shapes in the images. it obtain the P and S for each object and compare P/S ratio to template image and object.
Sobel use for P and finding edges and Labeling algorithm use for S. Platform: |
Size: 11264 |
Author:Mohammadali |
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Description: 二值图像连通域标记快速算法,能进行区域检测，附代说明文档-Binary image connected component labeling fast algorithm that can detect regional, with a generation of documentation Platform: |
Size: 47104 |
Author:lq8712b3 |
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Description: 二值图像连通域标记快速算法,能进行区域检测，附代说明文档，VB开发-Binary image connected component labeling fast algorithm that can detect regional, with a generation of documentation Platform: |
Size: 45056 |
Author:lq8712b3 |
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Description: 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 boundaries of the image, identifies the different particles. Platform: |
Size: 64512 |
Author:zhaofei |
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Description: 对二值图像进行连通域标记，然后根据面积，周长等特征进行分割。-labeling the connected region in a binary image, and then segment it by terms of area and border pixels. Platform: |
Size: 133120 |
Author:Haojie Wang |
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Description: 对图片以及视频帧进行连通域提取，环境需要opencv vs2005，必要的配置，连通域的算法是基于递归的二值图像标记算法。-Frame of the picture, and video connectivity components extraction, environmental needs opencv vs2005, the necessary configuration, connected components algorithm is based on the recursive binary image labeling algorithm. Platform: |
Size: 4498432 |
Author:王聪 |
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Description: 对灰度图像进行如下操作：去除图像的不均匀背景；用设置阈值的方法(thresholding)将结果图像转换成二值图像；通过成分标记(components labeling)返回图像中的目标对象属性，并计算目标对象的统计数字特征。-Gray-scale images of the following: removal of non-uniform image background the method used to set the threshold (thresholding) the result image is converted into binary image marked by elements (components labeling) to return the image of the target object property, and statistics calculated characteristics of the target object. Platform: |
Size: 1024 |
Author:赵宇 |
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Description: 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. Platform: |
Size: 173056 |
Author:王帅 |
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Description: 这里列举二值图像连通域标记算法包括直接扫描标记算法和二值图像连通域标记快速算法-Here are the binary image connected component labeling algorithm including direct scan labeling algorithm and a binary image connected component labeling fast algorithm Platform: |
Size: 66560 |
Author:宁静 |
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Search - binary image labeling