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Image Authentication Under Geometric Attacks Via Structure Matching
- Source :
- ICME
- Publication Year :
- 2005
- Publisher :
- IEEE, 2005.
-
Abstract
- Surviving geometric attacks in image authentication is considered to be of great importance. This is because of the vulnerability of classical watermarking and digital signature based schemes to geometric image manipulations, particularly local geometric attacks. In this paper, we present a general framework for image content authentication using salient feature points. We first develop an iterative feature detector based on an explicit modeling of the human visual system. Then, we compare features from two images by developing a generalized Hausdorff distance measure. The use of such a distance measure is crucial to the robustness of the scheme, and accounts for feature detector failure or occlusion, which previously proposed methods do not address. The proposed algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, common signal processing operations, global as well as local geometric transformations, and even hard to model distortions such as print and scan. Content changing (malicious) manipulations of image data are also accurately detected
- Subjects :
- Computer science
business.industry
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Hausdorff distance
Feature (computer vision)
Robustness (computer science)
Human visual system model
Computer vision
Artificial intelligence
business
Digital watermarking
Transformation geometry
Computer Science::Cryptography and Security
Data compression
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2005 IEEE International Conference on Multimedia and Expo
- Accession number :
- edsair.doi...........02bc904cec4c8659ba68c507c4cf77d3