Description: 包括图像的阈值分割，轮廓提取，标志物体测量面积和周长的源码。希望对各位有用。-Including the image threshold segmentation, contour extraction, logo objects, measuring area and perimeter of the source. Hope that useful to you. Platform: |
Size: 381952 |
Author:霞疙瘩228 |
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Description: Edge detection is one of the most commonly used operations in image analysis, and
there are probably more algorithms in the literature for enhancing and detecting edges
than any other single subject. The reason for this that edges form the outline of an
object. An edge is the boundary between an object and the background, and indicates
the boundary between overlapping objects. This means that if the edges in an image can
be identified accurately, all of the objects can be located and basic properties such as
area, perimeter, and shape can be measured. Since computer vision involves the
identification and classification of objects in an image, edge detections is an essential
tool. In this paper, we have compared several techniques for edge detection in image
processing. We consider various well-known measuring metrics used in image
processing applied to standard images in this comparison- Edge detection is one of the most commonly used operations in image analysis, and
there are probably more algorithms in the literature for enhancing and detecting edges
than any other single subject. The reason for this is that edges form the outline of an
object. An edge is the boundary between an object and the background, and indicates
the boundary between overlapping objects. This means that if the edges in an image can
be identified accurately, all of the objects can be located and basic properties such as
area, perimeter, and shape can be measured. Since computer vision involves the
identification and classification of objects in an image, edge detections is an essential
tool. In this paper, we have compared several techniques for edge detection in image
processing. We consider various well-known measuring metrics used in image
processing applied to standard images in this comparison Platform: |
Size: 448512 |
Author:Image |
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Description: 在图像中提取轮廓（用到了自适应阈值分割算法），根据目标特征，如周长、面积等参数进行筛选，得到目标的轮廓。-Contour extraction in the image (use an adaptive thresholding algorithm), depending on the target characteristics, such as perimeter, area and other parameters of screening, target profile. Platform: |
Size: 3934208 |
Author:风花雪月 |
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Description: 基于Matlab平台实现目标信息提取。求未含噪声的原图像的周长需先对图像进行二值化，然后选择一种算法进行边缘检测，包含prewitt,canny,sobel等算法，再通过sum(sum())函数进行周长的计算并显示在相应的位置。为求包含特定目标的噪声污染图像的周长或面积，首先对图像进行去噪，再进行二值化，接着进行微小分割，实现边缘提取或者区域分割，进一步统计目标周长或者目标面积。-Based on Matlab platform to achieve the goal of information extraction. Perimeter need to seek not contain the original noise image binarized image, and then select an algorithm for edge detection, including prewitt, canny, sobel algorithm, the circumference of the sum (sum ()) function calculated and displayed in the appropriate location. Seeking to contain a specific target image the perimeter or area of noise pollution, the first image noise, and then binarized, followed by small split, edge detection or region segmentation, and further statistical target circumference or target area.
Platform: |
Size: 1024 |
Author:李丽 |
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Description: shape of an image :
Shape factors are dimensionless quantities used in image analysis and microscopy that numerically describe the shape of a particle, independent of its size. Shape factors are calculated measured dimensions, such as diameter, chord lengths, area, perimeter, centroid, moments, etc.
-shape of an image :
Shape factors are dimensionless quantities used in image analysis and microscopy that numerically describe the shape of a particle, independent of its size. Shape factors are calculated measured dimensions, such as diameter, chord lengths, area, perimeter, centroid, moments, etc.
Platform: |
Size: 5120 |
Author:abdelali |
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Search - perimeter of an image