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Threshold selection by clustering gray levels of boundary

机译:通过对边界灰度进行聚类来进行阈值选择

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摘要

In this paper, threshold selection is considered in the continuous image rather than in digital image. We prove that, for each given object within 2D image, its optimal threshold is determined by the mean of the gray values of the points lying on its continuous boundary. Thus, we try to deduce threshold from the gray values of the boundary rather from the gray values of the given discrete sampling points (pixels or edge pixels). By the scheme, we well overcome some disadvantages existing in the threshold methods based on the histogram of edge pixels. Besides, the proposed method has the ability to well handle the image whose histogram has very unequal peaks and broad valley.
机译:在本文中,在连续图像而不是数字图像中考虑阈值选择。我们证明,对于2D图像内的每个给定对象,其最佳阈值由位于其连续边界上的点的灰度值的平均值确定。因此,我们尝试从边界的灰度值而不是给定离散采样点(像素或边缘像素)的灰度值推导出阈值。通过该方案,我们很好地克服了基于边缘像素直方图的阈值方法存在的一些缺点。此外,所提出的方法能够很好地处理直方图具有非常不相等的峰和宽谷的图像。

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