Document page decomposition using bounding boxes of connected components of black pixels
Document page decomposition using bounding boxes of connected components of black pixels
复制标题
使用黑色像素连通分量的边界框分解文档页面
DOI：
10.1117/12.205816
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
R. Haralick
中科院分区：
文献类型：
--
作者：
J. Ha;I. T. Phillips;R. Haralick
可以通过投影图像像素来执行文档图像的分割。这种像素投影方法是广泛使用的自上而下的分割方法之一，并且基于文档图像已被正确去歪斜的假设。不幸的是，像素投影方法在计算上是低效的。这是因为每个符号没有被视为一个计算单位。在本文中，我们解释了一种新的技术，这是高度战术性的剖析分析。我们不是投影图像像素，而是首先计算文档图像中每个连接组件的边界框，然后投影这些边界框。使用新技术，本文描述了如何提取单词、文本行和文本块（例如，段）。这种边界框投影方法与像素投影方法相比具有许多优点。它涉及的计算较少。当应用于文本区域时，还可以从投影轮廓推断边界框（以及因此图元符号）如何对齐和/或存在显著水平和垂直间隙的位置。由于新技术只处理边界框，因此它可以应用于任何非草书语言文档。
Segmentation of document images can be performed by projecting image pixels. This pixel projection approach is one of widely used top-down segmentation methods and is based on the assumption that the document image has been correctly deskewed. Unfortunately, the pixel projection approach is computationally inefficient. It is because each symbol is not treated as a computational unit. In this paper, we explain a new technique which is highly tactical in the profiling analysis. Instead of projecting image pixels, we first compute the bounding box of each connected component in a document image and then we project those bounding boxes. Using the new technique, this paper describes how to extract words, text lines, and text blocks (e.g., paragraphs). This bounding box projection approach has many advantages over the pixel projection approach. It is less computationally involved. When applied to text zones, it is also possible to infer from the projection profiles how bounding boxes (and, therefore, primitive symbols) are aligned and/or where significant horizontal and vertical gaps are present. Since the new technique manipulates only bounding boxes, it can be applied to any noncursive language documents.