| Title | Robust and discriminative image authentication based on standard model feature |
| Authors | Mou, Luntian Chen, Xilin Tian, Yonghong Huang, Tiejun |
| Affiliation | Key Lab. of Intell. Info. Process., ICT, CAS, Beijing, China Graduate University of CAS, Beijing, China National Engineering Laboratory for Video Technology, School of EE and CS, Peking University, Beijing, China |
| Issue Date | 2012 |
| Citation | 2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012.Seoul, Korea, Republic of. |
| Abstract | The goal of image authentication is to accept content-preserving operations and reject content-altering manipulations. So,it is increasingly approached by extracting content-based invariant features from original images and verifying their preservation in received images at later times. Since sparsity usually implies invariance, sparse feature representation has drawn significant attention from the research community. But only if discrimination is also found with a sparse feature, can it be successfully applied in image authentication. This paper proposes a sparse feature for image authentication by exploring the biologically-motivated standard model. Experimental results demonstrate both robustness and discrimination of the feature, and its effectiveness in tamper detection and location as well. ? 2012 IEEE. |
| URI | http://hdl.handle.net/20.500.11897/412269 |
| DOI | 10.1109/ISCAS.2012.6271431 |
| Indexed | EI |
| Appears in Collections: | 信息科学技术学院 |
