Low-Complexity Features for JPEG Steganalysis Using Undecimated DCT

By Vojtech Holub, Jessica J. Fridrich. IEEE Transactions on Information Forensics and Security, 2015

419 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/7caf1fd0a02d9f111be720efe053a6d83b8afc45

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Mo Chen
2. Yi Zhang
3. Xiangyang Luo
4. Xiaofeng Song
5. Fenlin Liu
6. Chunfang Yang
7. Mehdi Boroumand
8. Jessica J. Fridrich

Citations in the corpus

• Steganalysis of Adaptive JPEG Steganography Using 2D Gabor Filters (2015, methodology): “In addition, in literature [23, 17, 8, 13, 14], the final detection accuracy are all obtained by ensemble classifier [19] after features extraction.”
• Deep Residual Network for Steganalysis of Digital Images (2019, methodology): “[29], [30] and later improved by using Gabor filters for noise residual extraction [50], [59] and making them aware of the selection channel [15].”