首页> 外文会议>Pacific Rim International Conference on Artificial Intelligence; 20040809-20040813; Auckland; NZ >Improvement of Binarization Method Using a Water Flow Model for Document Images with Complex Backgrounds
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Improvement of Binarization Method Using a Water Flow Model for Document Images with Complex Backgrounds

机译:水流模型对复杂背景文档图像二值化方法的改进

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Binarization algorithm using a water flow model has been presented, in which a document image is efficiently separated into two regions, characters and backgrounds, due to the property of locally adaptive thresholding. However, this method has not decided when to stop the iterative process and required long processing time. Moreover, characters on poor contrast backgrounds often fail to be separated successfully. In the current paper, an improved approach is proposed to overcome above shortcomings of the existing method, by introducing a hierarchical thresholding technique as well as extracting the regions of interest (ROIs) for speed-up and an automatic stopping criterion.
机译:提出了一种使用水流模型的二值化算法,其中,由于局部自适应阈值的特性,文档图像被有效地分为两个区域:字符和背景。但是,该方法尚未确定何时停止迭代过程,并且需要较长的处理时间。此外,对比度背景差的字符通常无法成功分离。在当前的论文中,提出了一种改进的方法来克服现有方法的上述缺点,方法是引入分层阈值技术以及提取感兴趣区域(ROI)来加速和自动停止标准。

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