LOGO EXTRACTION USING COMBINED DISCRETE WAVELET TRANSFORM AND DYNAMIC STOCHASTIC RESONANCE

2013 ◽  
Vol 13 (01) ◽  
pp. 1350004
Author(s):  
RAJIB KUMAR JHA ◽  
PRABIR KUMAR BISWAS ◽  
B. N. CHATTERJI
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Stochastic Resonance ◽  
Signal Amplitude ◽  
Experimental Results ◽  
New Method ◽  
Discrete Wavelet ◽  
Noise Amplitude ◽  
Dynamic Stochastic Resonance ◽  
Dynamic Stochastic

In this paper, we have introduced a new method for watermark (logo) extraction from distorted watermarked images. The method is based on combined discrete wavelet transform (DWT) and dynamic stochastic resonance (DSR). In this method, the image property such as variance corresponding to the DWT coefficients of the image is tuned with the dynamic stochastic resonance parameters which causes resonance to the DWT coefficients. That is, the signal amplitude enhances and noise amplitude degraded in the DWT coefficients. This approach extracts hided logo from the distorted watermarked image which is almost very similar to the original logo. The experimental results have been compared with the existing techniques and were found to be superior.

WATERMARK DETECTION USING DYNAMIC STOCHASTIC RESONANCE

2013 ◽  
Vol 12 (03) ◽  
pp. 1350010 ◽  
Author(s):  
RAJIB KUMAR JHA ◽  
APOORV CHATURVEDI ◽  
RAJLAXMI CHOUHAN
Keyword(s):  
Stochastic Resonance ◽  
Spread Spectrum ◽  
Internal Noise ◽  
External Noise ◽  
Detection Technique ◽  
Discrete Wavelet ◽  
Detection Techniques ◽  
Dynamic Stochastic Resonance ◽  
Watermark Embedding ◽  
Dynamic Stochastic

In this paper, a dynamic stochastic resonance (DSR) based watermark detection technique in discrete wavelet transform (DWT) domain is presented. Pseudo random bit sequence having certain seed value is considered as a watermark. Watermark embedding is done by embedding random bits in spread-spectrum fashion to the significant DWT coefficients. Watermark detection is quantitatively characterized by the value of correlation. The performance of watermark detection is improved by DSR which is an iterative process that utilizes the internal noise present in the image or external noise which is added during attacks. Even under various noise attacks, geometrical distortions, image enhancement and compression attacks, the DSR-based random bits detection is observed to give noteworthy improvement over existing watermark detection techniques. DSR-based technique is also found to give better detection performance when compared with the suprathreshold stochastic resonance-based detection technique.

scholarly journals New method for denoising borehole transient electromagnetic data with discrete wavelet transform

2019 ◽  
Vol 168 ◽  
pp. 41-48 ◽  
Author(s):  
Xueping Dai ◽  
Li Zhen Cheng ◽  
Jean-Claude Mareschal ◽  
Daniel Lemire ◽  
Chong Liu
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
New Method ◽  
Discrete Wavelet ◽  
Electromagnetic Data ◽  
Transient Electromagnetic

AUDIO WATERMARKING WITH ANGLE QUANTIZATION BASED ON DISCRETE WAVELET TRANSFORM AND SINGULAR VALUE DECOMPOSITION

2018 ◽  
Vol 6 (2) ◽  
pp. 41-52
Author(s):  
Divya Chadar ◽  
Shailja Shukla
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Auditory System ◽  
Audio Signal ◽  
Singular Value ◽  
New Method ◽  
Discrete Wavelet ◽  
Audio Watermark ◽  
Value Decomposition

An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same. 

scholarly journals Digital Watermarking Algorithm Based on Wavelet Analysis

2013 ◽  
Vol 347-350 ◽  
pp. 2214-2217
Author(s):  
Qing Song Xu
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Rapid Development ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
A New Technique ◽  
Visual Properties ◽  
Watermarking Scheme

With the rapid development of the network and the multimedia technical , how to protect the security of the multimedia informations becomes the popular topic on studies. As a new technique used to protect the copyright of digital productions , the digital watermark technique has drawn extensive attention . A digital watermarking algorithm based on discrete wavelet transform (DWT) was presented according to human visual properties in the paper . Then some attack analyses were given. Experimental results show that the watermarking scheme proposed in this paper is invisible and robust to cropping, and also has good robustness to compression, filtering, and noise adding.

Using Iterative Discrete Wavelet Transform to Improve Trace Element Analysis by XRF Spectrometer

2021 ◽  
Vol 105 ◽  
pp. 79-89
Author(s):  
Qian Ma ◽  
Lian Liu ◽  
Fu Sheng Li ◽  
Yan Chun Zhao
Keyword(s):  
Wavelet Transform ◽  
Noise Reduction ◽  
Discrete Wavelet Transform ◽  
Trace Element ◽  
Background Noise ◽  
Limit Of Detection ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
X Ray ◽  
Fluorescence Spectrometer

X-ray fluorescence (XRF) spectrometry has certain difficulties of detecting trace amount material components accurately when measuring material samples composed of variable elements, mainly due to low Signal to Noise Ratio (SNR) issues of the characteristic spectroscopic peaks from the measurement. In this paper, a novel method called background noise reduction using Iterative Discrete Wavelet Transform (IDWT) methodology for trace element material analysis by advanced X-ray fluorescence spectrometer is proposed to improve SNR, thereby decreasing the Limit of Detection (LOD) for elemental qualitative analysis, and then achieve a more accurate quantitative analysis of trace elemental concentration. This paper utilized handheld X-ray fluorescence spectrometer to obtain the content of Sulphur in petroleum and 4 major pollution elements in soil. A total of 81 standard samples were collected and measured. The hardware parameters of the instrument were adjusted to optimize the SNR before background noise reduction. Experimental results illustrate that X-ray tube parameters have great influences on the calibration regression. Different X-ray tube voltages were tested and the optimal results were achieved at 5kV. Furthermore, IDWT algorithm was implemented and the optimal results were achieved by wavelet base “db5” and “sym4” with 7 level decomposition. The calibration regression curves were established for the Sulphur in petroleum. The regression R2 values after IDWT were increased effectively when compared with original data without IDWT. Finally, the experimental results demonstrate a very good linearity between the weight contents of the target material and the XRF spectral characteristic peak intensity, and also it is found the LOD for Sulphur in petroleum can be reduced when combing with the IDWT.

MONITORING MACHINING PROCESSES BASED ON DISCRETE WAVELET TRANSFORM AND STATISTICAL PROCESS CONTROL

2004 ◽  
Vol 02 (03) ◽  
pp. 299-311 ◽  
Author(s):  
XIAOLI LI ◽  
R. DU
Keyword(s):  
Wavelet Transform ◽  
Process Control ◽  
Discrete Wavelet Transform ◽  
Statistical Process Control ◽  
Control Charts ◽  
New Method ◽  
Discrete Wavelet ◽  
Machining Processes ◽  
Statistical Process ◽  
Shewhart Control

This paper presents a new method to monitor machining processes based on a combination of discrete wavelet transform (DWT) and statistical process control (SPC), called a multi-scale statistical approach. First, DWT is applied to decompose the sensor signal onto different scales. Next, the detection limits are formed for each decomposed signal components, called the sub-signals, using Shewhart control charts. Finally, by inverse wavelet transform of the threshold crossing points of the sub-signals, malfunctions can be detected. Based on a test on the tool condition monitoring in turning using acoustic emission (AE) signal, it is shown that the new method is effective and robust.

A Wavelet-Based Digital Watermarking Algorithm for Packaging Security

2012 ◽  
Vol 200 ◽  
pp. 660-665
Author(s):  
Shi Wei Liu ◽  
Zhen Liu ◽  
Qing Bao Wei
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Color Image ◽  
Digital Watermark ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
Point To Point ◽  
Watermark Algorithm

In this paper, a wavelet-based digital watermark algorithm for packaging security is proposed. In the algorithm, digital watermark is embedded in the color image CMYK mode, the method based on the discrete wavelet transform (DWT) can point to point semi-adaptive repeated embed digital watermark. Digital watermark that embedded in a color image can be extracted after printing, scanning and pre-processing the color image. The experimental results show that watermark extraction’s effect is acceptable, so the algorithm can achieve the purpose of the anti-counterfeiting for packaging printing. In addition the algorithm is robust enough against various kinds of attacks such as salt&pepper noise addition, JPEG compression, image crop and so on.

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