用于文档二值化的Niblack算法 [英] Niblack algorithm for Document binarization

问题描述

我有这张照片：

我正在尝试使用niblack算法进行文档二值化
我实现了简单的Niblack算法

and i'm trying to make Document binarization using niblack algorithm i've implemented the simple Niblack algorithm

T =平均值+ K * standardDiviation

T = mean + K* standardDiviation

这就是结果：

问题在于窗口中不包含任何对象的图像的某些部分，因此它将噪声检测为对象并对其进行详细说明。

the problem is there's some parts of the image in which the window doesn't contain any objects so it detects the noise as objects and elaborates them .

我尝试应用模糊滤镜然后进行全局阈值处理
结果是：

i tried to apply blurring filter then global thresholding that was the result :

其他任何过滤器都无法解决
i猜测唯一的解决办法是阻止算法检测全局噪声ndow我从对象中解脱

which wont be solved by any other filter i guess the only solution is preventing the algorithm from detecting global noise if the window i free from object

我有兴趣使用niblack算法不使用其他算法这样做任何建议吗？

i'm interested to do this using niblack algorithm not using other algorithm so any suggestions ?

推荐答案

我在本文中尝试过sauvola算法自适应文档图像二值化J. Sauvola *，M。 PietikaKinen第3.3节

i tried sauvola algorithm in this paper Adaptive document image binarization J. Sauvola*, M. PietikaKinen section 3.3

它是niblack算法的修改版本，它使用了修改后的niblack方程

it's a modified version of niblack algorithm which uses a modified equation of niblack

返回了相当不错的答案：

which returned a pretty good answers :

以及我尝试了对Niblack的另一个修改，它在本文中实现
：法国INSA大学里昂大学（C. 。 Wolf，JM Jolion）

as well as i tried another modification of Niblack which is implemented in this paper in the 5.5 Algorithm No. 9a: Université de Lyon, INSA, France (C. Wolf, J-M Jolion)

也取得了不错的结果：

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