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: 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: 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: This package contains some MatLab tools for multi-scale image
processing. Briefly, the tools include:
- Recursive multi-scale image decompositions (pyramids), including
Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These
operate on 1D or 2D signals of arbitrary dimension. Data
structures are compatible with the MatLab wavelet toolbox.
- Fast 2D convolution routines, with subsampling and boundary-handling.
- Fast point-operations, histograms, histogram-matching.
- Fast synthetic image generation: sine gratings, zone plates, fractals, etc.
- Display routines for images and pyramids. These include several
auto-scaling options, rounding to integer zoom factors to avoid
resampling artifacts, and useful labeling (dimensions and gray-range).
-This package contains some MatLab tools for multi-scale image
processing. Briefly, the tools include:
- Recursive multi-scale image decompositions (pyramids), including
Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These
operate on 1D or 2D signals of arbitrary dimension. Data
structures are compatible with the MatLab wavelet toolbox.
- Fast 2D convolution routines, with subsampling and boundary-handling.
- Fast point-operations, histograms, histogram-matching.
- Fast synthetic image generation: sine gratings, zone plates, fractals, etc.
- Display routines for images and pyramids. These include several
auto-scaling options, rounding to integer zoom factors to avoid
resampling artifacts, and useful labeling (dimensions and gray-range).
Platform: |
Size: 2065408 |
Author:not applicable |
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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: matlab下图像处理技术在智能交通中的应用 主要是小车的跟踪和标示-matlab image processing technology under the Intelligent Transportation System in the main car tracking and labeling Platform: |
Size: 522240 |
Author:fm |
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Description: Connected component labeling by an Iterative algorithm used for labeling image pixel.It will divide the region according to pixel value. Platform: |
Size: 10240 |
Author:Manish |
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Description: Read video into MATLAB using aviread and alculate the background image . Initialization for Kalman Filtering. Calculate the difference image to extract pixels with more thanthreshold change.
and Plot the tracking rectangle after Kalman filtering Platform: |
Size: 1024 |
Author:jack |
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Description: 区域分割、区域标记。可以标记灰度图像区域的重心，matlab实现，-Region segmentation, region labeling. Grayscale image area can mark the center of gravity, matlab achieve, Platform: |
Size: 1024 |
Author:李静 |
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Description: matlab图像处理求取叶片面积，包含去噪，二值化，连通域标记，去除小面积- MATLAB image processing to obtain blade area, including denoising, two value, connected domain labeling, removal of small area
Platform: |
Size: 4009984 |
Author:泰妍 |
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Search - Labeling image matlab