Singular Value Decomposition (SVD) based Image Tamper Detection Scheme
| Autor: | Sandeep Kaur, Alka Jindal |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Authentication
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 0102 computer and information sciences 02 engineering and technology 01 natural sciences Image (mathematics) Singular value Digital image 010201 computation theory & mathematics Computer Science::Computer Vision and Pattern Recognition Computer Science::Multimedia Diagonal matrix Singular value decomposition 0202 electrical engineering electronic engineering information engineering Code (cryptography) 020201 artificial intelligence & image processing Node (circuits) Artificial intelligence business |
| Zdroj: | 2020 International Conference on Inventive Computation Technologies (ICICT). |
| DOI: | 10.1109/icict48043.2020.9112432 |
| Popis: | Image authentication techniques are basically used to check whether the received document is accurate or actual as it was transmitted by the source node or not. Image authentication ensures the integrity of the digital images and identify the ownership of the copyright of the digital images. Singular Value Decomposition (SVD) is method based on spatial domain which is used to extract important features from an image. SVD function decomposes an image into three matrices (U, S, V), the S matrix is a diagonal matrix constitutes singular values. These values are important features of that particular image. The quick response code features are utilized to create QR code from the extracted values. The evaluations produced represents that this designed method is better in producing authenticated image as compared to existing schemes. |
| Databáze: | OpenAIRE |
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