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Historical document image restoration using multispectral imaging system

delete2013-08-01
delete77
PRE
AI
R
Rachid Hedjam *
M
Mohamed Cheriet
DOI:10.1016/j.patcog.2012.12.015delete
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摘要

摘要

En 中文
Thousands of valuable historical documents stored on the shelves of national libraries throughout the world are waiting to be scanned in order to facilitate access to the information they contain. The first major problem faced is degradation, which renders the visual quality of the document very poor, and in most cases, difficult to decipher. This work is part of our collaboration with the BAnQ (Bibliotheque et Archive Nationales de Quebec), which aims to propose a new approach to provide the end user (historian, scholars, researchers, etc.) with an acceptable visualization of these images. To that end, we have adopted a multispectral imaging system capable of producing images in invisible lighting, such as infrared lights. In fact, in addition to visible (color) images, the additional information provided by the infrared spectrum as well as the physical properties of the ink (used on these historical documents) will be further incorporated into a mathematical model, transforming the degraded image into its new clean version suitable for visualization. Depending on the degree of degradation, the problem of cleaning them could be resolved by image enhancement and restoration, whereby the degradation could be isolated in the Infrared spectrum, and then eliminated in the visible spectrum. The final color image is then reconstructed from the enhanced visible spectra (red, green and blue). The first experimental results are promising and our aim in collaboration with the BAnQ is to give this documentary heritage to the public and build an intelligent engine for accessing the documents. (C) 2013 Elsevier Ltd. All rights reserved.
Keyword:
Historical document images restoration
Ferro-gallic ink
Multispectral document Imaging
Multispectral image in-painting
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期刊

Pattern Recognition 封面图
Pattern Recognition
IF:
7.6
论文数:
1.3W
被引数:
4.5W

机构

U
university of quebec
学者数:
2.0W
论文数: 1.9W
被引数: 19
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