CFP last date
20 January 2025
Reseach Article

Manipulated Image Detection by using Scale Invariant Feature Detection Algorithm

by Swaleha B.chougale, Anis Mulla, Dhanashee V Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 105 - Number 12
Year of Publication: 2014
Authors: Swaleha B.chougale, Anis Mulla, Dhanashee V Patil
10.5120/18426-9784

Swaleha B.chougale, Anis Mulla, Dhanashee V Patil . Manipulated Image Detection by using Scale Invariant Feature Detection Algorithm. International Journal of Computer Applications. 105, 12 ( November 2014), 1-4. DOI=10.5120/18426-9784

@article{ 10.5120/18426-9784,
author = { Swaleha B.chougale, Anis Mulla, Dhanashee V Patil },
title = { Manipulated Image Detection by using Scale Invariant Feature Detection Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 105 },
number = { 12 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume105/number12/18426-9784/ },
doi = { 10.5120/18426-9784 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:11.008648+05:30
%A Swaleha B.chougale
%A Anis Mulla
%A Dhanashee V Patil
%T Manipulated Image Detection by using Scale Invariant Feature Detection Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 105
%N 12
%P 1-4
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

We deal with large amount of multimedia data either audio, video or image. In today's world seeing is no longer believing- the technology that allows for digital visual data to be manipulated is developing at great speed. The quick advance in image editing techniques has enabled people to synthesize realistic images conveniently. Some legal issues may arise when a manipulated image cannot be distinguished from original one by visual examination. In this paper Scale Invariant Feature Transform algorithm is used to extract interest points of an image. Voting procedure algorithm is used to determine transformation with respect to X-axis and Y-axis. Final results differentiates manipulated image from original image.

References
  1. Sebastiano Battiato, Giovanni Maria Farinella, Enrico Messina, and Giovanni, "Robust image alignment for tampering detection," IEEE Transactions on Information Forensics and Security, Vol. 7, no. 4, August 2012.
  2. D. G. Lowe, "Distinctive image features from scale-invariant key points," Int. J. Computer Vision, vol. 60, no. 2, pp. 91–110, 2004.
  3. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories," in Proc. IEEE Computer Soc. Conf. Computer Vision Pattern Recognition, 2006, pp. 2169–2178.
  4. M. Brown, R. Szeliski, and S. Winder, "Multi-image matching using multi-scale oriented patches," in Proc. IEEE Conf. Computer Vision Pattern Recognition, 2005, vol. 1, pp. 510–517.
  5. S. Battiato, G. M. Farinella, E. Messina, and G. Puglisi, "Robust image registration and tampering localization exploiting bag of features based forensic signature," in Proc. ACM Multimedia (MM'11), 2011.
  6. Online Available: http://www. google. co. in/
  7. A. K. Jain,"Fundamentals of Digital image processing", a book.
Index Terms

Computer Science
Information Sciences

Keywords

Image image editing techniques.