| 基于最大方差比的图像二值化算法 |
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| 引用本文： | 柴本成.基于最大方差比的图像二值化算法[J].浙江万里学院学报,2005,18(4):44-46,50. |
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| 作者姓名： | 柴本成 |
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| 作者单位： | 浙江万里学院,宁波,315100 |
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| 摘 要： | 提出了一种基于最大方差比的图像二值化算法,该方法将图像分成两个类,当类问方差与类内方差的分离度最大时即为最佳阂值.实验表明,该方法能够准确而快速地对图像进行二值化,特别是当对象物和背景的灰度值的差具有一定大小的时候,效果更明显.
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| 关 键 词： | 二值化 阈值 最大方差比 |
| 文章编号： | 1670-2250（2005）04-0044-03 |
| 收稿时间： | 2005-03-15 |
| 修稿时间： | 2005年3月15日 |
An Image Binarization Algorithm Based on Maximal Variance |
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| CHAI Ben-cheng.An Image Binarization Algorithm Based on Maximal Variance[J].Journal of Zhejiang Wanli University,2005,18(4):44-46,50. |
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| Authors: | CHAI Ben-cheng |
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| Abstract: | This paper proposes an image binarization algorithm based on maximal variance, which divides an image object into two classes and obtains its best threshold when the separation level between the inter-class variance and intra-class variance is maximal. The experiments illustrate the new algorithm can segment the image accurately and quickly, particularly in the case that the difference value of the image object between background and gray is certain in size. |
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| Keywords: | image binary threshold maximal variance |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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