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     Research Journal of Applied Sciences, Engineering and Technology


Identification and Inference of Cracks in Old Paintings Using Supervised Method

1S.P. Karuppiah and 2S.K. Srivatsa
1Jawaharlal Nehru Technological University, Hyderabad
2Prathyusha Institute of Technology and Management, Aranvoyalkuppam, Poonamallee-Tiruvallur Road, Tiruvallur-602 025, India
Research Journal of Applied Sciences, Engineering and Technology  2016  12:1176-1181
http://dx.doi.org/10.19026/rjaset.12.2874  |  © The Author(s) 2016
Received: March ‎12, ‎2015  |  Accepted: May ‎22, ‎2015  |  Published: June 15, 2016

Abstract

The older paintings are taken as input to find the crack and remove the crack using three steps: (a) identify crack (b) classify the crack (c) use trimmed median filter to get the quality of a rectified image. On many occasions the restoration of cracks in old paintings becomes a difficult task if it is done manually. So old paintings are digitized. It is evident that there is an increased need for carefully detailing the complexity of valuable sites with an improved accuracy. In the present paper a new effective methodology for digitizing the cracks that are caused by surrounding environment, particularly extreme changes in humidity and heat is presented. The digital paintings can be restored using different image processing techniques. When a painting is restored, the restorer must know which areas to be filled or recovered. MATLAB is used to build the code required to process and analyze the data. One of the most important findings of the paper is that the trimmed median filter technique is used to for the restoration of the digitized painting.

Keywords:

Cracks classification, image, painting, trimmed median filter,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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