Conference proceeding
Improved forgery detection with lateral chromatic aberration
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), v 2016-, pp 2024-2028
Mar 2016
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper we propose a technique to improve the accuracy of lateral chromatic aberration (LCA) based detection of copy-paste image forgeries. We propose a statistical model of the error between local estimates of LCA displacement vectors and those predicted by a global model. Using this statistical model, we formulate forgery detection as a hypothesis testing problem, and derive the optimal detection statistic for performing LCA-based forgery detection. Through a series of experiments, we demonstrate that our proposed technique outperforms existing approaches for conducting LCA-based forgery detection.
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Details
- Title
- Improved forgery detection with lateral chromatic aberration
- Creators
- Owen Mayer - Drexel UniversityMatthew Stamm - Drexel UniversityIEEE
- Publication Details
- 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), v 2016-, pp 2024-2028
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000388373402033
- Scopus ID
- 2-s2.0-84973300762
- Other Identifier
- 991019170318404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Acoustics
- Engineering, Electrical & Electronic