Demo Data from EDBT 2026 / reviewers in the wild / expert
Thi-Ngoc-Canh Doan
dblp:190/3387
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Digital forensics and information hiding · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video coding · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Digital forensics and information hiding › digital forensics › multimedia forensics › image forensics
JPEG compression forensics |
0.3 | 1 | 2017 | JPEG Quantization Step Estimation and Its Applications to Digital Image Forensics · IEEE Trans. Inf. Forensics Secur. 2017 |
Digital forensics and information hiding › digital forensics
multimedia forensics |
0.3 | 1 | 2017 | JPEG Quantization Step Estimation and Its Applications to Digital Image Forensics · IEEE Trans. Inf. Forensics Secur. 2017 |
Image and video coding
JPEG compression |
0.1 | 1 | 2017 | JPEG Quantization Step Estimation and Its Applications to Digital Image Forensics · IEEE Trans. Inf. Forensics Secur. 2017 |
Methods — techniques the papers use, named apart from their topics
DCT coefficient statistical modeling · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Image tampering detection based on a statistical model
Thi-Ngoc-Canh Doan, Florent Retraint, Cathel Zitzmann |
Multim. Tools Appl. | 1 |
| 2017 | JPEG Quantization Step Estimation and Its Applications to Digital Image ForensicsabstractThe goal of this paper is to propose an accurate method for estimating quantization steps from an image that has been previously JPEG-compressed and stored in lossless format. The method is based on the combination of the quantization effect and the statistics of discrete cosine transform (DCT) coefficient characterized by the statistical model that has been proposed in our previous works. The analysis of quantization effect is performed within a mathematical framework, which justifies the relation of local maxima of the number of integer quantized forward coefficients with the true quantization step. From the candidate set of the true quantization step given by the previous analysis, the statistical model of DCT coefficients is used to provide the optimal quantization step candidate. The proposed method can also be exploited to estimate the secondary quantization table in a double-JPEG compressed image stored in lossless format and detect the presence of JPEG compression. Numerical experiments on large image databases with different image sizes and quality factors highlight the high accuracy of the proposed method. Thanh Hai Thai, Rémi Cogranne, Florent Retraint, Thi-Ngoc-Canh Doan |
IEEE Trans. Inf. Forensics Secur. | 4 |