Multidirectional scratch detection and restoration in digitized old images
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
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
A template-based baseball video scene classification using efficient playfield segmentation
Multimedia Tools and Applications
Digital restoration of damaged mural images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this paper. 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 or controlled anisotropic diffusion is performed. The methodology has been shown to perform very well on digitized paintings suffering from cracks.