Robust Watermarking Algorithm Based on Hilbert-Huang Theory

2011 ◽  
Vol 255-260 ◽  
pp. 2291-2295
Author(s):  
Ming Hui Deng ◽  
Qing Shuang Zeng ◽  
Xiu Li Zhou
Keyword(s):  
Image Watermarking ◽  
Time Windows ◽  
Geometric Distortion ◽  
Frequency Change ◽  
Two Dimensional ◽  
Hilbert Huang Transform ◽  
Chirp Signals ◽  
Wigner Transformation ◽  
Robust Image ◽  
Frequency Properties

In this paper, we introduce a robust image watermarking method based on Hilbert-Huang Transform (HHT) against geometric distortion. This watermarking is detected by a linear frequency change. The HHT transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermark embedded in the HHT transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

Robust Watermarking Algorithm Based on Time-Frequency CHIRPLET

2011 ◽  
Vol 179-180 ◽  
pp. 881-885
Author(s):  
Ming Hui Deng ◽  
Qing Shuang Zeng ◽  
Yu Song
Keyword(s):  
Image Watermarking ◽  
Time Windows ◽  
Geometric Distortion ◽  
Frequency Change ◽  
Two Dimensional ◽  
Frequency Distributions ◽  
Time Frequency ◽  
Chirp Signals ◽  
Wigner Transformation ◽  
Frequency Properties

In this paper, a robust image watermarking method in two-dimensional time-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirplet transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermark embedded in the chirplet transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

The Image Watermarking against Shearing Based on Dopplerlet Transformation

2011 ◽  
Vol 181-182 ◽  
pp. 276-280
Author(s):  
Ming Hui Deng ◽  
Wen Zhe Li ◽  
Qi Chen Li
Keyword(s):  
Spatial Frequency ◽  
Dimensional Space ◽  
Image Watermarking ◽  
Time Windows ◽  
Geometric Distortion ◽  
Frequency Change ◽  
Two Dimensional ◽  
Frequency Distributions ◽  
Chirp Signals ◽  
Wigner Transformation

In this paper, a robust image watermarking method in two-dimensional space/spatial-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The dopplerlet transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermark embedded in the dopplerlet transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

Robust Image Information Identification Algorithm Based on Time-Frequency Transformation

2012 ◽  
Vol 616-618 ◽  
pp. 2214-2218
Author(s):  
Ming Hui Deng
Keyword(s):  
Image Watermarking ◽  
Geometric Distortion ◽  
Energy Concentration ◽  
Frequency Change ◽  
Identification Algorithm ◽  
Two Dimensional ◽  
Time Frequency ◽  
Chirp Signals ◽  
Wigner Transformation ◽  
Robust Image

In this paper, a robust image watermarking method with one-dimensional improved S transformation is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. We propose a modified Gaussian window which scales with the frequency in an efficient manner to provide improved energy concentration of the S-transform. The proposed scheme can resolve the time-frequency localization in a better way than the standard S transformation. The watermark is embedded in the 1D improved S transformation domains. The watermark thus generated is invisible and performs well in test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

Robust Time-Frequency Watermarking Based on Improved S Transformation

2011 ◽  
Vol 467-469 ◽  
pp. 146-151
Author(s):  
Ming Hui Deng ◽  
Qing Shuang Zeng ◽  
Yan Jun Li
Keyword(s):  
Image Watermarking ◽  
Geometric Distortion ◽  
Energy Concentration ◽  
Frequency Change ◽  
Two Dimensional ◽  
Efficient Manner ◽  
Time Frequency ◽  
Chirp Signals ◽  
Time Frequency Localization ◽  
Wigner Transformation

In this paper, a robust image watermarking method with one-dimensional improved S transformation is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. We propose a modified Gaussian window which scales with the frequency in an efficient manner to provide improved energy concentration of the S-transform. The proposed scheme can resolve the time-frequency localization in a better way than the standard S transformation. The watermark is embedded in the 1D improved S transformation domains. The watermark thus generated is invisible and performs well in test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

An Information Fusion Algorithm Based on Dopplerlet-Hough Transformation

2012 ◽  
Vol 605-607 ◽  
pp. 2211-2216
Author(s):  
Ming Hui Deng ◽  
Qing Shuang Zeng ◽  
Lan Ying Zhang
Keyword(s):  
Image Watermarking ◽  
Geometric Distortion ◽  
Energy Concentration ◽  
Frequency Change ◽  
Two Dimensional ◽  
Fusion Algorithm ◽  
Hough Transformation ◽  
Time Frequency ◽  
Chirp Signals ◽  
Wigner Transformation

In this paper, a robust image watermarking method with S-Hough transformation is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. We propose a modified Hough transformation to provide improved energy concentration of the Dopplerlet transform. The proposed scheme can resolve the time-frequency localization in a better way than the standard Dopplerlet transformation. The watermark is embedded in the 1D improved Dopplerlet transformation domains. The watermark thus generated is invisible and performs well in test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

Robust Image Information Identification Algorithm Based on Time-Frequency Chirplet-Radon Transformation

2012 ◽  
Vol 239-240 ◽  
pp. 950-954
Author(s):  
Ming Hui Deng ◽  
Qing Shuang Zeng ◽  
Lan Ying Zhang
Keyword(s):  
Spatial Frequency ◽  
Geometric Distortion ◽  
Frequency Change ◽  
Identification Algorithm ◽  
Two Dimensional ◽  
Time Frequency ◽  
Radon Transformation ◽  
Chirp Signals ◽  
Wigner Transformation ◽  
Robust Image

In this paper, a robust image watermarking method in two-dimensional space/spatial-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The one-dimensional chirplet transformation and radon transformation are used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermarks are embedded in the 1D Chirplet-Radon transformation domains. The watermark thus generated is invisible and performs well in StirMark test. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

Robust Watermarking Algorithm Based on Bi-Dimensional Empirical Mode Decomposition

2011 ◽  
Vol 204-210 ◽  
pp. 627-631
Author(s):  
Ming Hui Deng ◽  
Fang Yang ◽  
Run Tao Wang
Keyword(s):  
Empirical Mode Decomposition ◽  
Image Watermarking ◽  
Image Theory ◽  
Geometric Distortion ◽  
Robust Watermarking ◽  
Multi Scale ◽  
Mode Decomposition ◽  
Robust Image ◽  
Characteristics Of Image ◽  
Frequency Properties

In this paper, we introduce a robust image watermarking method based on bi-dimensional empirical mode decomposition against geometric distortion. Based on the characteristics of the image theory and human visual system, the proposed method makes use of orthogonal properties of empirical mode decomposition to achieve the bi-dimensional empirical mode decomposition transform on the image. The image is decomposed into a series of IMFs and residue which contain the different frequency parts of the image. So the watermark is adaptively weighed to the different positions of the middle frequency IMF region. The method makes use of the multi-scale analysis characteristics of image bi-dimensional empirical mode decomposition theory and the person’s sense of vision and shows excellent advantage against shearing attack. The method could show the watermark clearly when half of the image has been cut. Experimental results show this method excellent robustness for image shearing. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

scholarly journals Screen-Cam Robust Image Watermarking with Feature-Based Synchronization

2020 ◽  
Vol 10 (21) ◽  
pp. 7494
Author(s):  
Weitong Chen ◽  
Na Ren ◽  
Changqing Zhu ◽  
Qifei Zhou ◽  
Tapio Seppänen ◽  
...  
Keyword(s):  
Image Watermarking ◽  
Gaussian Function ◽  
Geometric Distortion ◽  
Low Pass ◽  
Feature Based ◽  
Robust Image ◽  
Watermarking Scheme ◽  
Watermark Synchronization ◽  
Desynchronization Attacks ◽  
Traditional Image

The screen-cam process, which is taking pictures of the content displayed on a screen with mobile phones or cameras, is one of the main ways that image information is leaked. However, traditional image watermarking methods are not resilient to screen-cam processes with severe distortion. In this paper, a screen-cam robust watermarking scheme with a feature-based synchronization method is proposed. First, the distortions caused by the screen-cam process are investigated. These distortions can be summarized into the five categories of linear distortion, gamma tweaking, geometric distortion, noise attack, and low-pass filtering attack. Then, a local square feature region (LSFR) construction method based on a Gaussian function, modified Harris–Laplace detector, and speeded-up robust feature (SURF) orientation descriptor is developed for watermark synchronization. Next, the message is repeatedly embedded in each selected LSFR by an improved embedding algorithm, which employs a non-rotating embedding method and a preprocessing method, to modulate the discrete Fourier transform (DFT) coefficients. In the process of watermark detection, we fully utilize the captured information and extract the message based on a local statistical feature. Finally, the experimental results are presented to illustrate the effectiveness of the method against common attacks and screen-cam attacks. Compared to the previous schemes, our scheme has not only good robustness against screen-cam attack, but is also effective against screen-cam with additional common desynchronization attacks.

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