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Adaptive thresholding to robust image binarization for degraded document images

机译:自适应阈值可对退化的文档图像进行鲁棒的图像二值化

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摘要

Owing to the elevated intra/inter variation among the foreground and background text of various document images, the text segmentation from the poorly degraded document images is the difficult job. This paper presents the document image binarization method by adaptive image contrast which is the integration of the local image gradient and the local image contrast which is lenient to background and text variation generated by various document degradations. Initially, an adaptive contrast map is constructed for the input degraded document image by the proposed document image binarization method. Then, the binarization is performed on this adaptive contrast map and the binarized contrast map is integrated with the Canny's edge map for determining the text stroke edge pixels. After that, depends on the local threshold which is defined by the identified text stroke edge pixels' intensities in the local window, the document text is divided. The proposed method is straight forward, vigorous, and it requires least amount of parameter tuning. The experimentation is performed on DIBCO 2011 dataset and the results of the experimentation show that the proposed method achieved high performance than the state-of-the-art methods.
机译:由于各种文档图像的前景和背景文本之间的内部/帧间差异增大,因此从质量较差的文档图像中进行文本分割是一项困难的工作。本文提出了一种通过自适应图像对比度对文档图像进行二值化的方法,该方法是将局部图像梯度和局部图像对比度进行整合,以适应各种文档降级产生的背景和文本变化。最初,通过提出的文档图像二值化方法为输入的降级文档图像构建自适应对比度图。然后,对该自适应对比度图执行二值化,并将二值化的对比度图与Canny边缘图集成在一起,以确定文本笔触边缘像素。之后,取决于由本地窗口中标识的文本笔触边缘像素的强度定义的局部阈值,对文档文本进行划分。所提出的方法简单,有力,并且需要最少的参数调整。在DIBCO 2011数据集上进行了实验,实验结果表明,该方法比最新方法具有更高的性能。

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