Abstract
Benford's Law (BL) has been proposed as a method to distinguish natural images from those that were altered in some way, through manipulation or distortion, after their acquisition. Another common use of BL is to detect artificially generated images. In this article, we evaluate the effectiveness of BL in the detection of Generative Artificial Intelligence (GAI) generated images. The images were generated in four different categories depending on the prompts to the GAI, namely original, artificial, cartoon-like and realistic. The results showed that only about 60% of the artificial images do not fit BL, while the other 40 % do. However, some very artificial looking images pass the threshold of BL. We hope that this article sheds some light on the topic of using BL for image forensics.
| Original language | English |
|---|---|
| Title of host publication | 2024 International Conference on Sustainable Technology and Engineering, i-COSTE 2024 |
| Publisher | IEEE Computer Society |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331517335 |
| ISBN (Print) | 9798331517342 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 10th IEEE International Conference on Sustainable Technology and Engineering - Murdoch University, Perth, Australia Duration: 18 Dec 2024 → 20 Dec 2024 https://i-coste.org/2024/ |
Publication series
| Name | 2024 International Conference on Sustainable Technology and Engineering, i-COSTE 2024 |
|---|
Conference
| Conference | 10th IEEE International Conference on Sustainable Technology and Engineering |
|---|---|
| Abbreviated title | i-COSTE 2024 |
| Country/Territory | Australia |
| City | Perth |
| Period | 18/12/24 → 20/12/24 |
| Internet address |
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