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A novel preprocessing method for hectography prints based on independent component analysis

机译:一种基于独立分量分析的拟合印刷品的新型预处理方法

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Archives and cultural facilities consists of vast spectra of different document classes, many of which are not encountered today anymore. The digitization therefore calls for image enhancement and preprocessing solutions so far not required and hence unsolved. A prominent document class in this context is hectography, which was an inexpensive printing and duplication method, widely used throughout the 20th century. The major challenge with hectography is poor contrast on the one side and multiple degradation effects on the other side. In this paper a novel preprocessing method for hectography duplicates is proposed which leads to better Optical Character Recognition (OCR) results compared to traditional methods that operate on grayscale images. The proposed method is based on a linear mixing model used in independent component analysis. The problem of unwanted Gaussian noise components is considered as well.
机译:档案和文化设施包括巨大的不同文档课程,其中许多人今天不再遇到。因此,数字化呼叫到目前为止不需要的图像增强和预处理解决方案,因此未解决。在此上下文中的一个突出的文档类是张非医学,这是一种廉价的印刷和重复方法,在整个20世纪中被广泛使用。张相拍摄的主要挑战在一侧对比度不佳,对另一方的多重降级效应。在本文中,提出了一种用于张非术的预处理方法,其导致更好的光学字符识别(OCR)结果与在灰度图像上运行的传统方法相比。该方法基于独立分量分析中使用的线性混合模型。也考虑了不需要的高斯噪声分量的问题。

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