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Crack detection and inpainting for virtual restoration of paintings: The case of the Ghent Altarpiece This publication appears in: Signal Processing Authors: B. Cornelis, T. Ruzic, E. Gezels, A. Dooms, A. Pizurica, L. Platisa, J. Cornelis, M. Martens, M. De Mey and I. Daubechies Volume: 93 Issue: Image Processing for Digital Art Work Pages: 605-619 Publication Date: Mar. 2013
Abstract: Digital image processing is proving to be of great help in the analysis and documentation of our vast cultural heritage. In this paper, we present a new method for the virtual restoration of digitized paintings with special attention for the Ghent Altarpiece (1432), a large polyptych panel painting of which very few digital reproductions exist. We achieve our objective by detecting and digitally removing cracks. The detection of cracks is particularly difficult because of the varying content features in different parts of the polyptych. Three new detection methods are proposed and combined in order to detect cracks of different sizes as well as varying brightness. Semi-supervised clustering based post-processing is used to remove objects falsely labelled as cracks. For the subsequent inpainting stage, a patch-based technique is applied to handle the noisy nature of the images and to increase the performance for crack removal. We demonstrate the usefulness of our method by means of a case study where the goal is to improve readability of the depiction of text in a book, present in one of the panels, in order to assist paleographers in its deciphering. External Link.
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