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matlab.thresholding-master

于 2019-04-14 发布 文件大小:23KB
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  在计算机视觉中,图像分割是将图像分成多个片段的过程。这使我们能够通过以比原始图像更简单的表示方式来更好地分析图像。一种用于分割图像的方法是阈值分割;也就是说,将强度值低于阈值的所有像素设置为背景值,而将高于阈值的其他像素设置为前景值。最简单的阈值处理形式是对所有像素使用全局阈值,而自适应阈值处理根据像素及其周围环境动态改变阈值。典型地,阈值处理从灰度图像开始,并输出二进制图像以清晰地描绘图像中的片段。在本实验中,我们开发了一种自适应阈值算法,并将其与更简单的算法进行了比较。 此外,我们还开发了逆运动学证明来将机械臂移动到给定的x,y,z坐标。这一证明涉及三种命名身份,并获得了对机械臂设计的更好理解。(Image threshold segmentation)

文件列表:

matlab.thresholding-master, 0 , 2017-11-17
matlab.thresholding-master\LICENSE, 35142 , 2017-11-17
matlab.thresholding-master\README.md, 62 , 2017-11-17
matlab.thresholding-master\adaptiveClustering.m, 5001 , 2017-11-17
matlab.thresholding-master\binaryFromLevels.m, 1012 , 2017-11-17
matlab.thresholding-master\complexedge.m, 622 , 2017-11-17
matlab.thresholding-master\graythreshn.m, 1825 , 2017-11-17
matlab.thresholding-master\hysteresisSegmentation.m, 359 , 2017-11-17
matlab.thresholding-master\imageHistEntropy.m, 1615 , 2017-11-17
matlab.thresholding-master\jaccardIndex.m, 1019 , 2017-11-17
matlab.thresholding-master\kapursegment.m, 1192 , 2017-11-17
matlab.thresholding-master\modActiveContour.m, 1121 , 2017-11-17
matlab.thresholding-master\phsBlobDiscrimination.m, 655 , 2017-11-17
matlab.thresholding-master\phsHysteresis.m, 809 , 2017-11-17
matlab.thresholding-master\script_OtsuMethod.m, 792 , 2017-11-17
matlab.thresholding-master\script_kapur.m, 682 , 2017-11-17
matlab.thresholding-master\script_testPappas.m, 4248 , 2017-11-17
matlab.thresholding-master\simpleAdaptiveSegmentation.m, 923 , 2017-11-17

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    说明:  基于自组织神经网络数据及图像处理,在图像分割中应用极强。很好的源程序。 (Self-organizing neural network-based data and image processing, image segmentation in the application of highly. Very good source.)
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