![]() ![]() Multiresolution analysis of ridges and valleys in grey-scale images. Digital inpainting based on the Mumford-Shah-Euler image model. Nontexture inpainting by curvature-driven diffusions. ![]() Median radial basis function neural network. ![]() Image processing for virtual restoration of artworks. Filling-in by joint interpolation of vector fields and gray levels. Keywords:Ĭracks classification, image, painting, trimmed median filter,īallester, C., M. One of the most important findings of the paper is that the trimmed median filter technique is used to for the restoration of the digitized painting. MATLAB is used to build the code required to process and analyze the data. When a painting is restored, the restorer must know which areas to be filled or recovered. The digital paintings can be restored using different image processing techniques. In the present paper a new effective methodology for digitizing the cracks that are caused by surrounding environment, particularly extreme changes in humidity and heat is presented. It is evident that there is an increased need for carefully detailing the complexity of valuable sites with an improved accuracy. On many occasions the restoration of cracks in old paintings becomes a difficult task if it is done manually. The older paintings are taken as input to find the crack and remove the crack using three steps: (a) identify crack (b) classify the crack (c) use trimmed median filter to get the quality of a rectified image. ![]()
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