Abstract
We are often required to retouch images in order to improve their visual appearance, by removing the visual discontinuities like breaks and damaged regions. Such retouching of images may be achieved by inpainting. Current techniques for image inpainting require the user to manually select the target regions to be inpainted. Very few techniques for automatically detecting the target regions for inpainting are reported in the literature, which are suitable to detect an actual damage or alteration to the given photograph. In this paper, we propose a Singular Value Decomposition (SVD) based novel technique for automatic detection of the damaged regions in the photographed object / scene, for the purpose of digitally restoring them to their entirety using inpainting. Results on an exhaustive set of images suggest that the mask generated using the proposed technique can be suitably used for inpainting purpose to digitally restore the given images.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C.: Image inpainting. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2000, pp. 417–424. ACM Press/Addison-Wesley Publishing Co., New York (2000)
Criminisi, A., Pérez, P., Toyama, K.: Region filling and object removal by exemplar-based image inpainting. IEEE Transactions on Image Processing 13, 1200–1212 (2004)
Pérez, P., Gangnet, M., Blake, A.: Poisson image editing. In: ACM SIGGRAPH 2003 Papers, SIGGRAPH 2003, pp. 313–318. ACM, New York (2003)
Grossauer, H.: A Combined PDE and Texture Synthesis Approach to Inpainting. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3022, pp. 214–224. Springer, Heidelberg (2004)
Shibata, T., Iketani, A., Senda, S.: Image Inpainting Based on Probabilistic Structure Estimation. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part III. LNCS, vol. 6494, pp. 109–120. Springer, Heidelberg (2011)
Padalkar, M.G., Joshi, M.V., Zaveri, M.A., Parmar, C.M.: Exemplar based inpainting using autoregressive parameter estimation. In: Proceedings of the International Conference on Signal, Image and Video Processing, ICSIVP 2012, IIT Patna, India, pp. 154–160 (2012)
Shih, T.K., Tang, N.C., Yeh, W.-S., Chen, T.-J., Lee, W.: Video inpainting and implant via diversified temporal continuations. In: Proceedings of the 14th Annual ACM International Conference on Multimedia, MULTIMEDIA 2006, pp. 133–136. ACM, New York (2006)
Chang, R.-C., Sie, Y.-L., Chou, S.-M., Shih, T.K.: Photo defect detection for image inpainting. In: Proceedings of the Seventh IEEE International Symposium on Multimedia, ISM 2005, pp. 403–407. IEEE Computer Society, Washington, DC (2005)
Tamaki, T., Suzuki, H., Yamamoto, M.: String-like occluding region extraction for background restoration. In: International Conference on Pattern Recognition, vol. 3, pp. 615–618 (2006)
Amano, T.: Correlation based image defect detection. In: Proceedings of the 18th International Conference on Pattern Recognition, ICPR 2006, pp. 163–166. IEEE Computer Society, Washington, DC (2006)
Parmar, C.M., Joshi, M.V., Raval, M.S., Zaveri, M.A.: Automatic image inpainting for the facial images of monuments. In: Proceedings of Electrical Engineering Centenary Conference 2011, IISc Bangalore, India, pp. 415–420 (2011)
Ammouche, A., Riss, J., Breysse, D., Marchand, J.: Image analysis for the automated study of microcracks in concrete. Cement and Concrete Composites 23, 267–278 (2001); Special Theme Issue on Image Analysis
Ringot, E., Bascoul, A.: About the analysis of microcracking in concrete. Cement and Concrete Composites 23, 261–266 (2001); Special Theme Issue on Image Analysis
Zou, Q., Cao, Y., Li, Q., Mao, Q., Wang, S.: Cracktree: Automatic crack detection from pavement images. Pattern Recognition Letters 33, 227–238 (2012)
Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. Journal of the American Society for Information Science 41, 391–407 (1990)
Wall, M.E., Rechtsteiner, A., Rocha, L.M.: Singular value decomposition and principal component analysis. In: Singular Value Decomposition and Principal Component Analysis, pp. 91–109. Kluwer, Norwell (2003)
Google Images (2012), http://www.images.google.com
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Padalkar, M.G., Zaveri, M.A., Joshi, M.V. (2013). SVD Based Automatic Detection of Target Regions for Image Inpainting. In: Park, JI., Kim, J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer Science, vol 7729. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37484-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-37484-5_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37483-8
Online ISBN: 978-3-642-37484-5
eBook Packages: Computer ScienceComputer Science (R0)