Morphological Top Hat Transform for Crack Removal in Digitized Paintings
This study explores the application of the Morphological Top Hat Transform to effectively remove cracks in digitized paintings. Cracks, characterized by low luminance and elongated structural features, are identified as local intensity minima, making them
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182 views • Feb 27, 2021
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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
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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
Video Information
Views
182
Duration
6:06
Published
Feb 27, 2021