多色文本二值化的自适应方法

Arindam Das, Sandipan Chowdhury
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引用次数: 1

摘要

本文介绍了我们在多色文本二值化方面的最新研究成果。在输出图像中,我们将前景内容表示为黑色,背景内容表示为白色,而不考虑原始图像中前景和背景的极性。本文采用基于连通分量分析的方法对边界框或边缘框内的单词或字符进行分组。本报告的主要新颖之处包括基于CIELAB颜色空间的局部颜色阈值计算每个边缘盒。这种方法使得所提出的系统能够对单个字符具有多种颜色的多颜色文本进行二值化。通过对知名的D1BCO2009和CMATERdb数据集进行定性对比研究,证明了该方法优于其他现有方法的有效性。
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Adaptive method for multi colored text binarization
This article presents our recent study on multi colored text binarization. In the output image, we represented foreground content as black and background as white regardless the polarity of foreground and background in original image. Here we applied connected component analysis based approach to group the words or characters within bounding or edge box. The main novelty of this reported work includes the calculation of each edge box based local color threshold value from CIELAB color space. This approach makes the proposed system capable of binarizing multi colored texts where a single character has more than one color. The proposed method has been executed on well-known D1BCO2009 and CMATERdb datasets that contain a large set of images to show the efficiency over other existing methods through qualitative comparison study.
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