退化文本-照片文档图像的智能阈值

Chun-Ming Tsai
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引用次数: 1

摘要

将纸质书的内容转换成数字形式是由数码相机或扫描仪捕捉到的。然而,在转换后,捕获的文档图像的照明往往分布不均匀。传统的阈值方法不能很好地阈值这类文档,通常是全文图像。如果降级的文档图像同时包含文本和照片,这些方法产生的二值化结果不令人满意。本文提出了一种高效的文本-照片文档图像降级智能阈值分割方法,包括:提出了灰度区域切割,将灰度文档图像智能分割成多个区域;采用区域阈值法对每个区域进行阈值处理;将灰度级文档图像转换为二值图像。实验结果表明,该方法在视觉测量中的性能优于现有的阈值分割方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligence thresholding for degraded text-photo document images
The conversion of the content from paper books into digital form is captured by digital cameras or scanners. However, after the conversion, the illumination of the captured document images is often unevenly distributed. Conventional thresholding methods cannot threshold these kind documents, usually full text images, properly. If the degraded document image includes both text and photo, these methods produce unsatisfactory binarizaion results. This paper presents an efficient and effective intelligent thresholding method for degraded text-photo document images, including: gray-level region cutting is proposed to segment the gray-level document image into several regions intelligently; each region is thresholded by using region thresholding; the gray-level document image is converted into a binary image. Experimental results show that the performance of the proposed method is better than other available thresholding methods in visual measurement.
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