Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contrast limited adaptive histogram equalization
Graphics gems IV
Markov random field modeling in computer vision
Markov random field modeling in computer vision
Evaluation of Methods for Ridge and Valley Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Image Processing for Virtual Restoration of Artworks
IEEE MultiMedia
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
Image inpainting by patch propagation using patch sparsity
IEEE Transactions on Image Processing
Virtual restoration of the ghent altarpiece using crack detection and inpainting
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Digital image processing techniques for the detection and removal of cracks in digitized paintings
IEEE Transactions on Image Processing
Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning
IEEE Transactions on Image Processing
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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.