Automatic thresholding of gray-level pictures using two-dimensional entropy
Computer Vision, Graphics, and Image Processing
Segmentation of Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Binarization and multithresholding of document images using connectivity
CVGIP: Graphical Models and Image Processing
Special issue on the analysis of historical documents
International Journal on Document Analysis and Recognition
RSLDI: Restoration of single-sided low-quality document images
Pattern Recognition
A multi-scale framework for adaptive binarization of degraded document images
Pattern Recognition
Document image binarization using background estimation and stroke edges
International Journal on Document Analysis and Recognition
Visual enhancement of old documents with hyperspectral imaging
Pattern Recognition
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
Novel Data Representation for Text Extraction from Multispectral Historical Document Images
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Hi-index | 0.01 |
Thousands of valuable historical documents stored on the shelves of national libraries throughout the world are waiting to be scanned in order to facilitate access to the information they contain.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additional information provided by the infrared spectrum as well as the physical properties of the ink (used on these historical documents) will be further incorporated into a mathematical model, transforming the degraded image into its new clean version suitable for visualization.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.