Proceedings of the 22nd International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2024, held in Bratislava, Slovak Republic, pp. 115-129 .
ISSN/ISBN: Not available at this time. DOI: 10.1007/978-3-031-78049-3_12
Abstract: This study evaluated Benford’slaw for detecting non-authentic digital images by analyzing the first digits of pixel values after a discrete cosine transform (DCT). We analyzed 137 pairs of authentic and modified JPEGs using ROC curves, k-means clustering, chi-squared tests, and PCA. The results showed AUC values near 0.5, indicating low classification performance. The k-means algorithm had 49% precision with low completeness, and PCA revealed a significant overlap between the authentic and manipulated images. These findings suggest the limited effectiveness of Benford’s law alone, highlighting the need to integrate advanced image-processing methods and explore additional pixel-distribution features for the effective detection of non-authentic images.
Bibtex:
@incollection{,
author = {Jarek Kobiela and Piotr M. Dzierwa},
title = {Application of Benford’s Law to the Identification of Non-authentic Digital Images},
booktitle = {Proceedings of the 22nd International Conference on Advances in Mobile Computing and Multimedia Intelligence}
publisher = {Springer Nature},
year = {2024},
pages = {115--129},
month = {dec}
doi = {10.1007/978-3-031-78049-3_12},
url = {https://link.springer.com/chapter/10.1007/978-3-031-78049-3_12},
}
Reference Type: Conference Paper
Subject Area(s): Image Processing