The binarization of historical documents is a difficult job due to the presence of many degradations. Many existing local binarization techniques use certain manually adjusted parameters. The output of these techniques is much dependent on the value of these parameters. One of such parameters is window size which is kept fixed for the whole text image. The fixed window size will not be able to perform well for images having variable stroke widths and text sizes. The proposed binarization technique (Modified Sauvola) is the modification of state of art Sauvola’s binarization technique. It automatically computes window size dynamically across the image pixel to pixel using the stroke width transform (SWT). This led to reduction in number of manually adjusted parameters. The results are compared with the nine existing techniques using the quantitative measures: FM, PSNR, NRM, MPM, and DRD. The results show that the proposed method outperforms existing methods for images having variable stroke widths and text sizes.

由于存在许多降级，历史文档的二值化是一项艰巨的工作。许多现有的本地二值化技术使用某些手动调整的参数。这些技术的输出很大程度上取决于这些参数的值。这样的参数之一是窗口大小，其对于整个文本图像保持固定。对于具有可变笔触宽度和文本大小的图像，固定的窗口大小将无法很好地执行。提出的二值化技术（改良的Sauvola）是对Sauvola的二值化技术的改进。它使用笔划宽度变换（SWT）自动在图像像素之间动态计算窗口大小。这减少了手动调整参数的数量。使用定量方法将结果与九种现有技术进行比较：FM，PSNR，NRM，MPM和DRD。结果表明，对于具有可变笔画宽度和文本大小的图像，该方法优于现有方法。