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Image Inpainting Using Robust Exemplar-based Technique

S.R. Gaonkar1 , P.D. Hire2 , P.S. Pimple3 , Y.R. Kotwal4 , B.A. Ahire5

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-4 , Page no. 176-179, Apr-2014

Online published on Apr 30, 2014

Copyright © S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire, “Image Inpainting Using Robust Exemplar-based Technique,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.176-179, 2014.

MLA Style Citation: S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire "Image Inpainting Using Robust Exemplar-based Technique." International Journal of Computer Sciences and Engineering 2.4 (2014): 176-179.

APA Style Citation: S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire, (2014). Image Inpainting Using Robust Exemplar-based Technique. International Journal of Computer Sciences and Engineering, 2(4), 176-179.

BibTex Style Citation:
@article{Gaonkar_2014,
author = {S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire},
title = {Image Inpainting Using Robust Exemplar-based Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2014},
volume = {2},
Issue = {4},
month = {4},
year = {2014},
issn = {2347-2693},
pages = {176-179},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=133},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=133
TI - Image Inpainting Using Robust Exemplar-based Technique
T2 - International Journal of Computer Sciences and Engineering
AU - S.R. Gaonkar, P.D. Hire, P.S. Pimple, Y.R. Kotwal, B.A. Ahire
PY - 2014
DA - 2014/04/30
PB - IJCSE, Indore, INDIA
SP - 176-179
IS - 4
VL - 2
SN - 2347-2693
ER -

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Abstract

Image in-painting is the art of restoring lost and selected parts of an image based on the background information in such a way so that the change is not observed by the observer. Image in-painting techniques is used in many fields like heritage preservation, films etc. In this paper, we are using exemplar based inpainting algorithm, this approach propagates the image information from the known region into the missing region at patch level. We first note that exemplar-based texture synthesis contains the essential process required to replicate both texture and structure; the success of structure propagation, however, is highly dependent on the order in which the filling proceeds. The existing algorithms are combined to improve the efficiency for finding the line association in selected region. Main focus is on data term and confidence term to find association in selected region which is to be inpainted. The region filling is done from that line associated to other section in selected region.

Key-Words / Index Term

Image Inpainting, Robust-Exemplar Inpainting, Image Segmentation, Object Removal

References

[1] Shivali Tyagi ,Sachin Singh , �Image Inpainting By Optimized Exemplar Region Filling Algorithm�,IJSCE IISN:2231-2307,Volume -2,Issue-6,January 2013
[2] Muthukumar S, Dr. Krishnan N., Pasupati P., Deepa S., �Analysis of Image inpainting techniques with Exemplar, Poisson and successive elimination and 8 pixel neighbourhood method� IJCA(0975-8887),Volume -9,No.11, November 2010
[3] Pranali Dhabekar, Geeta Salunke, �The Exemplar-based Image Inpainting algorithm through Patch Progation�,IJRTE ISSN:2277-3878,Volume-1, Issue-4,Octomber-2012
[4] Zongben Xu, Jain Sun, �Image Inpainting by Patch Propagation Using Patch Sparsity� IEEE Transactions on Image processing ,vol. 19, No.5,May 2010
[5] R. Mart�ınez-Noriega, A. Roumy, G. Blanchard, �Exemplar-based image inpainting: fast priority and coherent nearest neighbour search�, 2012 IEEE International Workshop on Machine Learning for signal Processing, September.23-26,Satandar, Spain.
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