Morphological Top Hat Transform for Crack Removal in Digitized Paintings

DESIGN DETAILS Cracks usually have low luminance and, thus, can be considered as local intensity minima with rather elongated structural characteristics. Therefore, a crack detector can be applied on the luminance component of an image and should be able to identify such minima. A crack-detection procedure based on top-hat transform is used in this Matlab design. The cracks are detected by thresholding (graythresh Global image threshold using Otsu's method) the output of the morphological top-hat transform. Afterward, the thin dark brush strokes which have been misidentified as cracks are removed using neural network. Finally, crack filling using order Median and Vector Median filter diffusion is performed. The performance is evaluated by PSNR. REFERENCES Reference Paper-1: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digitized Paintings Author’s Name: Ioannis Giakoumis, Nikos Nikolaidis, and Ioannis Pitas Source: IEEE Year: 2006 Reference Paper-1: Detection and Removal of Cracks in Digitized Paintings Author’s Name: Rakshama J Bhingi Source: Thesis- Goa University Year: 2013 Request source code for academic purpose, fill REQUEST FORM below, http://www.verilogcourseteam.com/request-form You may contact +91 7904568456 by WhatsApp Chat, for paid services. We are available on Telegram and Signal. Visit Website: http://www.verilogcourseteam.com/ Visit Our Social Media Like our Facebook Page: https://www.facebook.com/VerilogCourseTeam/ Subscribe: https://www.youtube.com/verilogcourseteamelectricalprojects Subscribe: https://www.youtube.com/verilogcourseteammatlabproject Subscribe: https://www.youtube.com/verilogcourseteam