Abstract— The restoration of paintings and manuscripts is defined as the process of restoring old and damaged artworks and documents exhibiting cracks. Cracks are caused by three factors; aging, drying up of painting material, and mechanical. It is necessary that cultural heritages be restored to their original or a near-original state. To enhance the overall quality of the image, there are different techniques and methodologies that can be used for conservation and restoration. The main objective of this study is to analyse techniques and methodologies that have been developed for the detection, classification of small patterns, and restoration of cracks in digitized old painting and manuscripts. The purpose of this research is to present previous works on detection and restoration of cracks using image processing techniques and methodologies.

minimizing noises from images to restore it and increase its quality is a crucial step. For this, an efficient algorithms were proposed to remove noises such as (salt pepper, Gaussian, and speckle) noises from grayscale images. The algorithm did that by selecting a window measuring 3x3 as the center of processing pixels, other algorithms did that by using median filter (MF), adopted median filter (AMF), adopted weighted filter (AWF), and the adopted weighted median filter (AWMF). The results showed that the proposed algorithm compares to previous algorithms by having a better signal-to-noise ratio (PSNR).

Ancient paintings are cultural heritage that can be preserved via computer aided analysis and processing. These paintings deteriorate due to undesired cracks, which are caused by aging, drying up of painting material, and mechanical factors. These heritages need to be restored to their respective original or near-original states. There are different techniques and methodologies that can be used to conserve and restore the overall quality of these images. The main objective of this study is to analyze techniques and methodologies that have been developed for the detection, classification of small patterns, and restoration of cracks in digitized old painting and manuscripts. The purpose of the developed algorithm is to identify cracks using the thresholding operation, which was the output of the top-hat transform morphology. Afterwards, the breaks, which were wrongly identified as cracks, were separated for utilization in a semi-automatic procedure based on region growth. Finally, both the median filter and weighted median techniques were applied to fill the cracks and enhance image quality.