A Multiple-Expert Binarization Framework for Multispectral Images

In this work, a multiple-expert binarization framework for multispectral images is proposed. The framework is based on a constrained subspace selection limited to the spectral bands combined with state-of-the-art gray-level binarization methods. The framework uses a binarization wrapper to enhance the performance of the gray-level binarization. Nonlinear preprocessing of the individual spectral bands is used to enhance the textual information. An evolutionary optimizer is considered to obtain the optimal and some suboptimal 3-band subspaces from which an ensemble of experts is then formed. The framework is applied to a ground truth multispectral dataset with promising results. In addition, a generalization to the cross-validation approach is developed that not only evaluates generalizability of the framework, it also provides a practical instance of the selected experts that could be then applied to unseen inputs despite the small size of the given ground truth dataset.Comment: 12 pages, 8 figures, 6 tables. Presented at ICDAR'1

Readability Enhancement and Palimpsest Decipherment of Historical Manuscripts

This paper presents image acquisition and readability enhancement techniques for historical manuscripts developed in the interdisciplinary project “The Enigma of the Sinaitic Glagolitic Tradition” (Sinai II Project).1 We are mainly dealing with parchment documents originating from the 10th to the 12th centuries from St. Cather- ine’s Monastery on Mount Sinai. Their contents are being analyzed, fully or partly transcribed and edited in the course of the project. For comparison also other mss. are taken into consideration. The main challenge derives from the fact that some of the manuscripts are in a bad condition due to various damages, e.g. mold, washed out or faded text, etc. or contain palimpsest (=overwritten) parts. Therefore, the manuscripts investigated are imaged with a portable multispectral imaging system. This non-invasive conservation technique has proven extremely useful for the exami- nation and reconstruction of vanished text areas and erased or washed o palimpsest texts. Compared to regular white light, the illumination with speci c wavelengths highlights particular details of the documents, i.e. the writing and writing material, ruling, and underwritten text. In order to further enhance the contrast of the de- graded writings, several Blind Source Separation techniques are applied onto the multispectral images, including Principal Component Analysis (PCA), Independent Component Analysis (ICA) and others. Furthermore, this paper reports on other latest developments in the Sinai II Project, i.e. Document Image Dewarping, Automatic Layout Analysis, the recent result of another project related to our work: the image processing tool Paleo Toolbar, and the launch of the series Glagolitica Sinaitica

Analytical and mathematical methods for revealing hidden details in ancient manuscripts and paintings: A review

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings

Understanding multispectral imaging of cultural heritage:Determining best practice in MSI analysis of historical artefacts

Although multispectral imaging (MSI) of cultural heritage, such as manuscripts, documents and artwork, is becoming more popular, a variety of approaches are taken and methods are often inconsistently documented. Furthermore, no overview of the process of MSI capture and analysis with current technology has previously been published. This research was undertaken to determine current best practice in the deployment of MSI, highlighting areas that need further research, whilst providing recommendations regarding approach and documentation. An Action Research methodology was used to characterise the current pipeline, including: literature review; unstructured interviews and discussion of results with practitioners; and reflective practice whilst undertaking MSI analysis. The pipeline and recommendations from this research will improve project management by increasing clarity of published outcomes, the reusability of data, and encouraging a more open discussion of process and application within the MSI community. The importance of thorough documentation is emphasised, which will encourage sharing of best practice and results, improving community deployment of the technique. The findings encourage efficient use and reporting of MSI, aiding access to historical analysis. We hope this research will be useful to digitisation professionals, curators and conservators, allowing them to compare and contrast current practices

Multispectral imaging and analysis of the Archimedes Palimpsest

The Archimedes Palimpsest is a manuscript that has been preserved for approximately 1,000 years. Among its pages are some of the few known sources of treatises from the Greek mathematician Archimedes. The writing has been overwritten with prayer text, called the Euchologion, and portions of the faded Archimedes text are difficult to read. This research investigates methods to detect the presence of ink in the Archimedes Palimpsest using state-of-the-art image processing techniques applied to data from X-ray fluorescence (XRF) scans. In an effort to extract more legible text, various methods of imaging have been applied to the Archimedes manuscript. Recent X-ray fluorescence images of the palimpsest suggest the possibility of detecting individual text layers and isolating them from each other. This is encouraging, since many of the pages have also been partially masked by gold-leafed, Byzantine-style artwork, making the Archimedes writing difficult to see with the human eye. The scans measure the X radiation emitted by atoms on the pages that have been excited by other higher energy X rays incident to the parchment. This caused certain elements within the manuscript, such as the iron in the ink, to fluoresce at energies that are specific to the particular material. A total of 2,000 different energy levels, or bands, were recorded. To evaluate the data contained in this large number of bands, a single data set was created that included all bands, referred to as a datacube, which shows the transition of each pixel through the spectrum. Special image processing tools, developed for use in the field of remote sensing to process aerial and satellite data, can be used to detect certain patterns within the datacube. Each tool is then used to segregate the noise from the relevant data in the datacube. The datacube for this thesis research was created from a small portion of one page of the Archimedes Palimpsest, and may inherently be subject to certain noise limitations. This study focuses on two main objectives: Evaluation of X-ray fluorescence data to determine which energy levels contain useful information about the layers of text. Creation of a pseudocolored composite RGB image of a portion of enhanced Archimedes text, similar to previous pseudocolored MSI images. Results from this study show that only a few regions within the datacube contain information relevant to the layers of text. Certain algorithms, such as principal component analysis and minimum noise fraction, showed distinct information about trace elements fluorescing in the ink and parchment. Meaningful data near the spectral line of each trace element was detected after disbanding the datacube into smaller regions. Enough information was obtained as a result to create colorized RGB composite images that enhance the contrast of the Archimedes writing relative to the overwritten text. It is hoped that this research can improve the method for identifying useful bands of information within datacubes. The research may also have created a repeatable method for detecting useful bands of information in similar datacubes. State-of-the-art multispectral imaging applications were specifically applied to detect, extract, and enhance previously illegible writings that are of interest to scholars and museums in particular

DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning

This paper presents a novel iterative deep learning framework and apply it for document enhancement and binarization. Unlike the traditional methods which predict the binary label of each pixel on the input image, we train the neural network to learn the degradations in document images and produce the uniform images of the degraded input images, which allows the network to refine the output iteratively. Two different iterative methods have been studied in this paper: recurrent refinement (RR) which uses the same trained neural network in each iteration for document enhancement and stacked refinement (SR) which uses a stack of different neural networks for iterative output refinement. Given the learned uniform and enhanced image, the binarization map can be easy to obtain by a global or local threshold. The experimental results on several public benchmark data sets show that our proposed methods provide a new clean version of the degraded image which is suitable for visualization and promising results of binarization using the global Otsu's threshold based on the enhanced images learned iteratively by the neural network.Comment: Accepted by Pattern Recognitio

Image and Video Processing for Cultural Heritage

Charvillat V., Tonazzini A., Van Gool L., Nikolaidis N., ''Editorial: Image and video processing for cultural heritage'', EURASIP journal on image and video processing, vol. 2009, Article ID 163064, 3 pp., 2010.status: publishe