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- Special Effects
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- File Size:
- 449kb
- Update:
- 2018-04-15
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Description: The largest between-class variance method was proposed by the Japanese scholar Nobuyuki Otsu in 1979. It is an adaptive threshold determination method, also known as the Otsu method, or OTSU for short. It is based on the grayscale characteristics of the image and divides the image into two parts: the background and the target. The larger the variance between the background and the target, the greater the difference between the two parts that make up the image. When the part of the target is wrongly divided into backgrounds or part of the background is mis-divided into goals, the difference between the two parts will be smaller. Therefore, the segmentation that maximizes the variance between classes means that the probability of wrong division is the smallest.
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| Filename | Size | Date |
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| 自适应阈值\adaptivethreshold.m | 687 | 2012-02-06
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| 自适应阈值\baihe.jpg | 168694 | 2011-07-03
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| 自适应阈值\ex1.m | 347 | 2012-02-06
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| 自适应阈值\ex2.m | 386 | 2012-02-06
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| 自适应阈值\ex3.m | 1278 | 2012-02-06
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| 自适应阈值\ex4.m | 120 | 2012-02-06
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| 自适应阈值\hehua.JPG | 27660 | 2011-07-03
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| 自适应阈值\kmeans.m | 954 | 2012-02-06
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| 自适应阈值\medtest.png | 53631 | 2008-03-06
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| 自适应阈值\moli.jpg | 62567 | 2011-07-03
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| 自适应阈值\regiongrowing.m | 1610 | 2018-03-06
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| 自适应阈值\shuixian.jpg | 149852 | 2011-07-03
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| 自适应阈值\thresh_md.m | 855 | 2012-02-06
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| 自适应阈值\Untitled.m | 132 | 2018-03-06
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| 自适应阈值\程序调用说明.doc | 28672 | 2012-09-26
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| 自适应阈值 | 0 | 2018-04-15 |
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