Advancement on Damage-Less Watermark Extraction Using Non-Linear Feature Extraction Scheme Trained on Frequency Domain

Digital Rights Management ◽

10.4018/978-1-4666-2136-7.ch020 ◽

2013 ◽

pp. 436-460

Author(s):

Kensuke Naoe ◽

Yoshiyasu Takefuji

Keyword(s):

Digital Watermarking ◽

Copyright Protection ◽

Visual Images ◽

Detailed Data ◽

Linear Feature ◽

Multimedia Contents ◽

Linear Feature Extraction ◽

Content Identification ◽

Extraction Scheme ◽

Image Integrity

The proposed method contributes to secure image digital watermarking for content identification without damaging or losing any detailed data of visual images. The features of our proposed method employ an application to authenticate multimedia, similarity comparison, verification of image integrity and copyright protection of multimedia contents.

Download Full-text

Blind Image Watermarking in Canonical and Cepstrum Domains Based on 4-Connected t-o’clock Scrambling

Symmetry ◽

10.3390/sym12020266 ◽

2020 ◽

Vol 12 (2) ◽

pp. 266

Author(s):

Farhana Shirin Chowdhury ◽

Pranab Kumar Dhar ◽

Kaushik Deb ◽

Takeshi Koshiba

Keyword(s):

Digital Watermarking ◽

Copyright Protection ◽

Image Watermarking ◽

Superior Performance ◽

Easy Access ◽

Multimedia Content ◽

Watermark Image ◽

Tree Property ◽

Multimedia Contents ◽

Blind Image

Copyright protection of multimedia content is confronted with great challenges such as easy access to the Internet. Digital watermarking is widely applicable technique for copyright protection of multimedia contents. In this paper, a blind symmetric watermarking method in canonical and cepstrum domains based on four-connected t-o’clock scrambling is proposed. Initially, the watermark image is scrambled using the four-connected t-o’clock method to enhance the security. Then, the rotation operation is applied to the host image to extract the region where the watermark bits are embedded. After that, discrete linear canonical transform (DLCT) is applied to the extracted region to obtain the DLCT region. Cepstrum transform (CT) is performed on DLCT region to attain CT region. The CT region is then divided into non-overlapping blocks. The watermark bits are inserted into each block using max-heap and min-heap tree property. Experimental results illustrate that the proposed method shows high robustness against numerous attacks. Moreover, it produces high quality watermarked images and provides high security. Furthermore, it has superior performance to recent methods in terms of imperceptibility, robustness, and security.

Download Full-text

Structural Damage Classification in a Jacket-Type Wind-Turbine Foundation Using Principal Component Analysis and Extreme Gradient Boosting

Sensors ◽

10.3390/s21082748 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2748

Author(s):

Jersson X. Leon-Medina ◽

Maribel Anaya ◽

Núria Parés ◽

Diego A. Tibaduiza ◽

Francesc Pozo

Keyword(s):

Principal Component Analysis ◽

Feature Extraction ◽

Wind Turbine ◽

Structural Damage ◽

Principal Component ◽

Gradient Boosting ◽

Damage Classification ◽

Linear Feature ◽

Linear Feature Extraction ◽

Extreme Gradient Boosting

Damage classification is an important topic in the development of structural health monitoring systems. When applied to wind-turbine foundations, it provides information about the state of the structure, helps in maintenance, and prevents catastrophic failures. A data-driven pattern-recognition methodology for structural damage classification was developed in this study. The proposed methodology involves several stages: (1) data acquisition, (2) data arrangement, (3) data normalization through the mean-centered unitary group-scaling method, (4) linear feature extraction, (5) classification using the extreme gradient boosting machine learning classifier, and (6) validation applying a 5-fold cross-validation technique. The linear feature extraction capabilities of principal component analysis are employed; the original data of 58,008 features is reduced to only 21 features. The methodology is validated with an experimental test performed in a small-scale wind-turbine foundation structure that simulates the perturbation effects caused by wind and marine waves by applying an unknown white noise signal excitation to the structure. A vibration-response methodology is selected for collecting accelerometer data from both the healthy structure and the structure subjected to four different damage scenarios. The datasets are satisfactorily classified, with performance measures over 99.9% after using the proposed damage classification methodology.

Download Full-text

A DCT-Domain System for Digital Watermarking

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.321-324.2609 ◽

2013 ◽

Vol 321-324 ◽

pp. 2609-2612

Author(s):

Yan Liang ◽

Gao Yan ◽

Chun Xia Qi

Keyword(s):

Signal Processing ◽

Digital Watermarking ◽

Copyright Protection ◽

Random Sequence ◽

Multimedia Data ◽

Dct Domain ◽

Digital Document ◽

Dct Coefficients ◽

Processing Techniques ◽

Signal Processing Techniques

Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia data in a networked environment. It makes possible to tightly associated to a digital document a code allowing the identification of the data creator, owner, authorized consumer, and so on. In this paper a new DCT-domain system for digital watermarking algorithm for digital images is presented: the method, which operates in the frequency domain, embeds a pseudo-random sequence of scrambled image in a selected set of DCT coefficients. After embedding, the watermark is adapted to the image by exploiting the masking characteristics of the human visual system, thus ensuring the watermark invisibility. By exploiting the statistical properties of the embedded sequence, the mark can be reliably extracted without resorting to the original uncorrupted image. Experimental results demonstrate that the watermark is robust to several signal processing techniques, including JPEG compression, cut, fuzzy, addition of noise, and sharpen.

Download Full-text

Edge detection and linear feature extraction using a 2-D random field model

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/34.23115 ◽

1989 ◽

Vol 11 (1) ◽

pp. 84-95 ◽

Cited By ~ 73

Author(s):

Y.T. Zhou ◽

V. Venkateswar ◽

R. Chellappa

Keyword(s):

Feature Extraction ◽

Edge Detection ◽

Random Field ◽

Field Model ◽

Random Field Model ◽

Linear Feature ◽

Linear Feature Extraction

Download Full-text

Digital Watermarking for 3D Polygonal Model Based on Wavelet Transform

Volume 2: 19th Computers and Information in Engineering Conference ◽

10.1115/detc99/cie-9031 ◽

1999 ◽

Author(s):

Hiroaki Date ◽

Satoshi Kanai ◽

Takeshi Kishinami

Keyword(s):

Wavelet Transform ◽

Digital Watermarking ◽

Copyright Protection ◽

Affine Transformation ◽

Wavelet Coefficient ◽

Original Data ◽

Geometric Error ◽

Digital Data ◽

Cad Cam ◽

Polygonal Model

Abstract Recently, much interest is being taken in a method to protect the copyright of digital data and prevent illegal duplication of it. However, in the area of CAD/CAM and CG, there are no effective ways to protect the copyright of the 3D geometric models. As a first step to solve this problem, a new digital watermarking method for 3D polygonal models is introduced in this paper. Watermarking is one of the copyright protection methods where an invisible watermark is secretly embedded into the original data. The proposed watermarking method is based on the wavelet transform (WT) and multi-resolution representation (MRR) of the polygonal model. The watermark can be embedded in the large wavelet coefficient vectors at various resolution levels of the MRR. This makes the embedded watermark imperceptible and invariant to the affine transformation, and also makes the control of the geometric error caused by the watermarking reliable.

Download Full-text