NDLI: A robust RST invariant image watermarking method based on locally detected features

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2015 IEEE International Symposium on Haptic, Audio and Visual Environments and Games (HAVE)

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A robust RST invariant image watermarking method based on locally detected features

Content Provider	IEEE Xplore Digital Library
Author	Yan Liu Jiying Zhao
Copyright Year	2005
Description	Author affiliation: Sch. of Inf. Technol. & Eng., Ottawa Univ., Canada (Yan Liu; Jiying Zhao)
Abstract	This paper presents a robust rotation, scaling and translation (RST) invariant image watermarking method based on locally detected features. First, the feature points are detected in the original image by using the Harris corner detection. Then, the Delaunay tessellation is created on these feature points. Watermark data are embedded and detected in each of the Delaunay triangles. The Harris corner detection is the key point in this scheme. Traditionally, the global threshold is used for the Harris corner detection. As a result, the points are concentrated on areas with rich texture information and the contrast change within the image. In this way, the locations of points are seriously affected by attacks, such as, geometrical attacks. It makes the watermark detection difficult or even impossible. In order to generate more robust feature points, we use a local threshold feature detection method, in which local thresholds are used for different parts of the target image. The feature points are almost uniformly distributed on the image. The experimental results show that this method makes feature points very robust after geometrical attacks, JPEG compression and noise addition.
File Size	1090616
File Format	PDF
ISBN	0780393767
DOI	10.1109/HAVE.2005.1545666
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-01
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Watermarking Computer vision Haptic interfaces Digital images Noise robustness Transform coding Image coding Protection Robot vision systems Detectors
Content Type	Text
Resource Type	Article

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