Digital watermarking
A Stochastic Approach to Content Adaptive Digital Image Watermarking
IH '99 Proceedings of the Third International Workshop on Information Hiding
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A feature-based robust digital image watermarking scheme
IEEE Transactions on Signal Processing
Robust template matching for affine resistant image watermarks
IEEE Transactions on Image Processing
Rotation, scale, and translation resilient watermarking for images
IEEE Transactions on Image Processing
Region-based image watermarking
IEEE Transactions on Image Processing
Geometrically invariant watermarking using feature points
IEEE Transactions on Image Processing
Geometric Invariance in image watermarking
IEEE Transactions on Image Processing
Robust image watermarking based on generalized Radon transformations
IEEE Transactions on Circuits and Systems for Video Technology
Improved content-based watermarking using scale-invariant feature points
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
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This paper addresses feature-based image watermarking methods for digital contents. Most previous watermarking algorithms suffer from geometric distortion attacks that desynchronize the location of the inserted watermark. In order to synchronize the watermark location, watermark synchronization should be performed. One solution for watermark synchronization is to use image features. This paper describes a feature-based watermarking method based on scale-invariant keypoints. We extract feature points from the scale-invariant keypoint extractor and then decompose feature points into a set of disjoint triangles. These triangles are watermarked by an additive spread-spectrum method on the spatial domain. We perform an intensive simulation in comparison with other feature-based watermarking methods using 100 test images. Results show that the proposed method is considerably robust against both geometric distortion attacks and signal processing attacks listed in Stirmark 3.1.