04-12-2012, 04:06 PM
DETECTION AND REMOVAL OF CRACKS IN DIGITIZED PAINTINGS
DETECTION AND REMOVAL.doc (Size: 1.69 MB / Downloads: 62)
ABSTRACT
An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this project. The cracks are detected by thresholding the output of the morphological top-hat transform. Afterward, the thin dark brush strokes which have been misidentified as cracks are removed using either a median radial basis function neural network on hue and saturation data or a semi-automatic procedure based on region growing.
Finally, crack filling using order statistics filters such as median filter is performed. The methodology has been shown to perform very well on digitized paintings suffering from cracks.
Overview of the System
Many paintings, especially old ones, suffer from breaks in the substrate, the paint, or the varnish. These patterns are usually called cracks or craquelure and can be caused by aging, drying, and mechanical factors. Age cracks can result from nonuniform contraction in the canvas or wood-panel support of the painting, which stresses the layers of the painting. Drying cracks are usually caused by the evaporation of volatile paint components and the consequent shrinkage of the paint. Finally,mechanical cracks result from painting deformations due to external causes, e.g., vibrations and impacts. The appearance of cracks on paintings deteriorates the perceivedimage quality.
However, one can use digital image processing techniques to detect and eliminate the cracks on digitized paintings. Such a “virtual” restoration can provide clues to art historians, museum curators and the general public on how the painting would look like in its initial state, i.e., without the cracks. Furthermore, it can be used as a nondestructive tool for the planning of the actual restoration. The user should manually select a point on each crack to be restored.Other research areas that are closely related to crack removal include image inpainting which deals with the reconstruction of missing or damaged image areas by filling in information from the neighboring areas, and disocclusion, i.e., recovery of object parts that are hidden behind other objects within an image.
Methods developed in these areas assume that the regions where information has to be filled in are known The former are usually based on partial differential equations (PDEs) and on the calculus of variations whereas the latter rely on texture synthesis principles. A technique that decomposes the image to textured and structured areas and uses appropriate interpolation techniques depending on the area where the missing information lies has also been proposed . The results obtained by these techniques are very good. A methodology for the restoration of cracks on digitized paintings, which adapts and integrates a number of image processing and analysis tools is proposed in this paper.
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