Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Cited by Google
- Similars in SciELO
- Similars in Google
Share
Revista Facultad de Ingeniería Universidad de Antioquia
Print version ISSN 0120-6230On-line version ISSN 2422-2844
Abstract
CORTES-OSORIO, Jimmy Alexander; CHAVES-OSORIO, José Andrés and LOPEZ-ROBAYO, Cristian David. Hybrid Algorithm for the detection of Pixel-based digital image forgery using Markov and SIFT descriptors. Rev.fac.ing.univ. Antioquia [online]. 2022, n.105, pp.111-121. Epub June 07, 2023. ISSN 0120-6230. https://doi.org/10.17533/udea.redin.20211165.
Today, image forgery is common due to the massification of low-cost/high-resolution digital cameras, along with the accessibility of computer programs for image processing. All media is affected by this issue, which makes the public doubt the news. Though image modification is a typical process in entertainment, when images are taken as evidence in a legal process, modification cannot be considered trivial. Digital forensics has the challenge of ensuring the accuracy and integrity of digital images to overcome this issue. This investigation introduces an algorithm to detect the main types of pixel-based alterations such as copy-move forgery, resampling, and splicing in digital images. For the evaluation of the algorithm, CVLAB, CASIA V1, Columbia, and Columbia Uncompressed datasets were used. Of 7100 images evaluated, 3666 were unaltered, 791 had resampling, 2213 had splicing, and 430 had copy-move forgeries. The algorithm detected all proposed forgery pixel methods with an accuracy of 91%. The main novelties of the proposal are the reduced number of features needed for identification and its robustness for the file format and image size.
Keywords : Copy-Move; Markov; Resampling; SIFT; Splicing.