Luigi Bedini

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We propose a novel approach to restoring digital document images, with the aim of improving text legibility and OCR performance. These are often compromised by the presence of artifacts in the background, derived from many kinds of degradations, such as spots, underwritings, and show-through or bleed-through effects. So far, background removal techniques(More)
Ancient documents are usually degraded by the presence of strong background artifacts. These are often caused by the so-called bleed-through effect, a pattern that interferes with the main text due to seeping of ink from the reverse side. A similar effect, called show-through and due to the nonperfect opacity of the paper, may appear in scans of even(More)
We implement an Independent Component Analysis (ICA) algorithm to separate signals of different origin in sky maps at several frequencies. Due to its self-organizing capability, it works without prior assumptions either on the frequency dependence or on the angular power spectrum of the various signals; rather, it learns directly from the input data how to(More)
This paper deals with blind separation of images from noisy linear mixtures with unknown coefficients, formulated as a Bayesian estimation problem. This is a flexible framework, where any kind of prior knowledge about the source images and the mixing matrix can be accounted for. In particular, we describe local correlation within the individual images(More)
This paper reports some of the results obtained by applying statistical processing techniques to multispectral images of the Archimedes palimpsest. We focused on the possibilities of extracting the faint and highly degraded underwritten text, which constitutes the most ancient source for several treatises by Archimedes. Assuming each image to be generated(More)
This paper proposes an integrated system for the processing and analysis of highly degraded printed documents for the purpose of recognizing text characters. As a case study, ancient printed texts are considered. The system is comprised of various blocks operating sequentially. Starting with a single page of the document, the background noise is reduced by(More)
Blind Source Separation techniques, based both on Independent Component Analysis and on second order statistics, are presented and compared for extracting partially hidden texts and textures in document images. Barely perceivable features may occur, for instance, in ancient documents previously erased and then re-written (palimpsests), or for transparency(More)