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Title: Image Processing Techniques for the detection and Removal of cracks in Dizitized Pain
Page Link: Image Processing Techniques for the detection and Removal of cracks in Dizitized Pain -
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Created at: Tuesday 30th of March 2010 12:10:48 AM
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Title: Detection and Removal of Cracks in Digitized Paintings
Page Link: Detection and Removal of Cracks in Digitized Paintings -
Posted By: project topics
Created at: Monday 02nd of May 2011 01:52:11 PM
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Detection and Removal of Cracks in Digitized Paintings
IEEE Transactions on Image Processing, Vol. 15, No. 1, January 2006
Language: VB.NET

Abstract:
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 o ....etc

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Title: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti
Page Link: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti -
Posted By: computer science crazy
Created at: Friday 18th of September 2009 12:45:32 AM
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Digital Image Processing Techniques for the Detection and Removal of Cracks in Digitized Paintings
Abstract: An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this project. The cracks are detected by threshold 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. F ....etc

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Title: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti
Page Link: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti -
Posted By: electronics seminars
Created at: Wednesday 13th of January 2010 10:21:30 AM
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Digital Image Processing Techniques for the Detection and Removal of Cracks in Digitized Paintings

Abstract: An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this project. The cracks are detected by threshold 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 ....etc

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Title: detection and removal of cracks in digitized image
Page Link: detection and removal of cracks in digitized image -
Posted By: sweetchap_suresh
Created at: Sunday 04th of April 2010 03:06:41 AM
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Title: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti
Page Link: Digital Image Processing Techniques for the Detection and Removal of Cracks in Digiti -
Posted By: hemanthsa
Created at: Tuesday 24th of November 2009 12:40:57 PM
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Title: earthquake dection using fm radio
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Posted By: bhargav123
Created at: Sunday 02nd of January 2011 01:34:37 PM
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Title: Collision Dection and avoidance
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Posted By: nikunj_me
Created at: Saturday 21st of August 2010 12:24:10 AM
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Title: Removal of cracks in digitized paintings
Page Link: Removal of cracks in digitized paintings -
Posted By: AAFIYA_KALEEM
Created at: Wednesday 30th of March 2011 01:15:07 PM
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Title: Digital image processing techniques for the detection and removal of cracks in digiti
Page Link: Digital image processing techniques for the detection and removal of cracks in digiti -
Posted By: seminar surveyer
Created at: Thursday 23rd of September 2010 07:40:25 PM
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Presented by
Ioannis Giakoumis, Nikos Nikolaidis, Ioannis Pitas
Department of Informatics
Aristotle University of Thessaloniki


Abstract
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. Afterwards, the thin dark brush strokes which have been mis identified as cracks are removed using either a Median Radial Basis Function (MRBF) neural network on hue and saturation ....etc

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