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Scalable structure learning via context-free recursive document decomposition

机译:可扩展结构通过无背景递归文档分解学习

摘要

An approach is provided in which the approach aggregates a set of pixel values from a bitmap image into a set of row sum values and a set of column sum values. The bitmap image is a pixelated representation of a document. The approach applies a localized Fourier transform to the set of row sum values and the set of column sum values to generate frequency representations of the set of row sum values and the set of frequency sum values. The approach decomposes the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations, and sends the set of image portions to a text recognition system.
机译:提供一种方法,其中该方法将一组像素值从位图图像聚合到一组行和值和一组列和值。 位图图像是文档的像素化表示。 该方法将本地化的傅里叶变换应用于一组行和值和列和值集,以生成行和值集的频率表示和频率总和值的集合。 该方法基于在该组频率表示中识别的至少一个分离位置,将位图图像分解为一组图像部分,并将该组图像部分发送到文本识别系统。

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