ICTACT Journal on Image and Video Processing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Removal of Unwanted Objects from Images using Statistics


Affiliations
1 Department of Computer Engineering, Pune Institute of Computer Technology, India
     

   Subscribe/Renew Journal


Nowadays with cheap digital cameras and the easy availability of camera enabled smartphones, people have been taking a lot of photos. But many a times, it happens that the photos clicked have some unwanted objects appearing in the picture that either partially or completely obscure the subject or their presence spoils the quality of the photo in some or the other way. Modern powerful image editors and in-painting algorithms are capable enough to remove these abnormalities in post-processing to provide a convincing output image. But these often include manual work which makes them time-consuming. Also, these either require an expert user or some complex algorithms for their functioning. The algorithms and methods discussed in this paper aim to provide a much simpler approach to solve these problems using basic statistics. A comparative analysis of their efficiency is also provided.

Keywords

Image Processing, Statistics, Image Stacking.
Subscription Login to verify subscription
User
Notifications
Font Size

  • S. Ravi, P. Pasupathi, S. Muhukumar and N. Krishnan “Image In-Painting Techniques-A Survey and Analysis”, Proceedings of 9th International Conference on Innovations in Information Technology, pp. 1-6, 2013.

  • V.V. Nabiyev, A. Tasci and M. Ulutas, “Removing Unwanted Objects from an Image”, Proceedings of 19th International Conference on Signal Processing and Communications Applications, pp. 1-7, 2011.

  • L.B. Bangaru and V. Gupta, “Object Removal by Kriging Interpolation Technique”, Proceedings of International Conference on Cognitive Computing and Information Processing, pp. 1-4, 2015.

  • A. Criminisi, P. Prez and K. Toyama, “Object Removal by Exemplar-Based Inpainting”, Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 721-728, 2003.

  • M. Bertalmio, G. Sapiro, V. Caselles and C. Ballester, “Image Inpainting”, Proceedings of International Conference on Graphics and Interactive Techniques, pp. 417-424, 2000.

  • A. Criminisi, P. Perez and K. Toyama, “Region Filling and Object Removal by Exemplar-Based Image Inpainting”, IEEE Transactions on Image Processing, Vol. 13, No. 9, pp. 233-246, 2004.

  • R. Witte, “Statistics”, 10th Edition, Wiley, 2017.

  • Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing”, 2nd Edition, Pearson, 2007.

  • B.D. Dent, “Cartography”, McGraw-Hill, 2007.

  • G.F. Jenks, “Generalization in Statistical Mapping”, Annals of the Association of American Geographers, Vol. 53, No. 1, pp. 15-26, 1963.

  • G.F. Jenks, “The Data Model Concept in Statistical Mapping”, International Yearbook of Cartography, Vol. 7, pp. 186-190, 1967.


Abstract Views: 230

PDF Views: 1




  • Removal of Unwanted Objects from Images using Statistics

Abstract Views: 230  |  PDF Views: 1

Authors

Sourav Kulkarni
Department of Computer Engineering, Pune Institute of Computer Technology, India

Abstract


Nowadays with cheap digital cameras and the easy availability of camera enabled smartphones, people have been taking a lot of photos. But many a times, it happens that the photos clicked have some unwanted objects appearing in the picture that either partially or completely obscure the subject or their presence spoils the quality of the photo in some or the other way. Modern powerful image editors and in-painting algorithms are capable enough to remove these abnormalities in post-processing to provide a convincing output image. But these often include manual work which makes them time-consuming. Also, these either require an expert user or some complex algorithms for their functioning. The algorithms and methods discussed in this paper aim to provide a much simpler approach to solve these problems using basic statistics. A comparative analysis of their efficiency is also provided.

Keywords


Image Processing, Statistics, Image Stacking.

References