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首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Document representation and its application to page decomposition
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Document representation and its application to page decomposition

机译:文档表示及其在页面分解中的应用

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摘要

Transforming a paper document to its electronic version in a form suitable for efficient storage, retrieval, and interpretation continues to be a challenging problem. An efficient representation scheme for document images is necessary to solve this problem. Document representation involves techniques of thresholding, skew detection, geometric layout analysis, and logical layout analysis. The derived representation can then be used in document storage and retrieval. Page segmentation is an important stage in representing document images obtained by scanning journal pages. The performance of a document understanding system greatly depends on the correctness of page segmentation and labeling of different regions such as text, tables, images, drawings, and rulers. We use the traditional bottom-up approach based on the connected component extraction to efficiently implement page segmentation and region identification. A new document model which preserves top-down generation information is proposed based on which a document is logically represented for interactive editing, storage, retrieval, transfer, and logical analysis. Our algorithm has a high accuracy and takes approximately 1.4 seconds on a SGI Indy workstation for model creation, including orientation estimation, segmentation, and labeling (text, table, image, drawing, and ruler) for a 2550/spl times/3300 image of a typical journal page scanned at 300 dpi. This method is applicable to documents from various technical journals and can accommodate moderate amounts of skew and noise.
机译:将纸质文档转换为适合有效存储,检索和解释的格式的电子文档仍然是一个难题。一个有效的文档图像表示方案对于解决此问题是必要的。文档表示涉及阈值化,倾斜检测,几何布局分析和逻辑布局分析技术。然后可以将派生的表示形式用于文档存储和检索。页面分割是表示通过扫描日记页面获得的文档图像的重要阶段。文档理解系统的性能在很大程度上取决于页面分割和标注不同区域(如文本,表格,图像,图形和标尺)的正确性。我们使用基于连接的组件提取的传统的自下而上的方法来有效地实现页面分割和区域识别。提出了一种保留自上而下的生成信息的新文档模型,基于该模型逻辑上表示文档以进行交互式编辑,存储,检索,传输和逻辑分析。我们的算法具有很高的准确性,并且在SGI Indy工作站上花费约1.4秒进行模型创建,包括2550 / spl次/ 3300图像的方向估计,分割和标记(文本,表格,图像,图形和标尺)。典型的日记本页面以300 dpi扫描。此方法适用于来自各种技术期刊的文档,并且可以容纳适度的偏斜和噪声。

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