Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Splicing Forgery Detection and the Impact of Image Resolution
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Context: There has been a rise in the usage of digital images these days. Digital images are being used in many areas like in medicine, wars, etc. As the images are being used to make many important decisions, it is necessary to know if the images used are clean or forged. In this thesis, we have considered the area of splicing forgery. In this thesis, we are also considering and analyzing the impact of low-resolution images on the considered algorithms.

Objectives. Through this thesis, we try to improve the detection rate of splicing forgery detection. We also examine how the examined splicing forgery detection algorithm works on low-resolution images and considered classification algorithms (classifiers).

Methods: The research methods used in this research are Implementation and Experimentation. Implementation was used to answer the first research question i.e., to improve the detection rate in splicing forgery. Experimentation was used to answer the second research question. The results of the experiment were analyzed using statistical analysis to find out how the examined algorithm works on different image resolutions and on the considered classifiers.

Results: One-tailed Wilcoxon signed rank test was conducted to compare which algorithm performs better, the T+ value obtained was less than To so the null hypothesis was rejected and the alternative hypothesis which states that Algorithm 2 (our enhanced version of the algorithm) performs better than Algorithm 1 (original algorithm), is accepted. Experiments were conducted and the accuracy of the algorithms in different cases were noted, ROC curves were plotted to obtain the AUC parameter. The accuracy, AUC parameters were used to determine the performance of the algorithms.

Conclusions: After the results were analyzed using statistical analysis, we came to the conclusion that Algorithm 2 performs better than Algorithm 1 in detecting the forged images. It was also observed that Algorithm 1 improves its performance on low-resolution images when trained on original images and tested on images of different resolutions but, in the case of Algorithm 2, its performance is improved when trained and tested on images of the same resolution. There was not much variance in the performance of both of the algorithms on images of different resolution. Coming to the classifiers, Algorithm 1 improves its performance on linear SVM whereas Algorithm 2 improves its performance when using the simple tree classifier.

Place, publisher, year, edition, pages
2017. , 46 p.
Keyword [en]
Splicing Forgery, Machine Learning, Image Processing
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-14060OAI: oai:DiVA.org:bth-14060DiVA: diva2:1085560
Subject / course
DV2566 Master's Thesis (120 credits) in Computer Science
Educational program
DVAXA Master of Science Programme in Computer Science
Presentation
2017-01-23, J1620, Blekinge Institute of Technology SE-371 79 Karlskrona, Sweden, Karlskrona, 10:00 (English)
Supervisors
Examiners
Available from: 2017-03-31 Created: 2017-03-29 Last updated: 2017-03-31Bibliographically approved

Open Access in DiVA

fulltext(943 kB)77 downloads
File information
File name FULLTEXT02.pdfFile size 943 kBChecksum SHA-512
476607c96b52c35ee396d40919b98d4b4f7f2f0a9b20dc93f7dbb1c407695458591b9277fe8698666e4e3ba0b576d44c4225d070a162bc711f12977957f81fc9
Type fulltextMimetype application/pdf

By organisation
Department of Computer Science and Engineering
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 77 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 108 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf