scholarly journals Discrete Wavelet Transform and a Singular Value Decomposition Technique for Watermarking Based on an Adaptive Fuzzy Inference System

2017 ◽  
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Decomposition Technique ◽  
Inference System ◽  
Value Decomposition

scholarly journals Implementasi Teknik Watermarking Menggunakan Metode Discrete Wavelet Transform (DWT) dan Singular Value Decomposition (SVD) pada Citra Digital

2021 ◽  
Vol 14 (2) ◽  
pp. 125
Author(s):  
Verryna Adzillatul Fathiha
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Value Decomposition

Watermarking merupakan teknik penyembunyian data/informasi kedalam suatu citra digital yang tidak kasat mata atau tidak dapat diketahui secara visual. Penyembunyian data/informasi kedalam citra tersebut bersifat rahasia. Karena tahan terhadap proses digitalisasi, teknik watermarking dapat digunakan untuk melindungi kepemilikan suatu citra digital. Ada tiga kriteria yang harus diperhatikan dalam watermarking pada citra digital, diantaranya adalah security, impreceptibily, dan robustness. Pada tugas Penulisan Karya Ilmiah (PI) ini dibuat suatu program watermarking menggunakan metode Discrete Wavelet Transform (DWT) dan Singular Value Decomposition (SVD) yang kemudian juga akan dipaparkan bagaimana cara menggunakan program watermarking yang telah dibuat. Keunggulan dari program ini citra yang digunakan dalam program watermarking ini dapat berupa citra berwarna maupun citra grayscale. Program watermarking ini dibuat menggunakan bahasa pemrograman C++ melalui aplikasi Matlab Kata Kunci            : Wateramarking , Singular Value Decomposition (SVD), Discrete Wavelet Transform (DWT), Matlab, Bahasa Pemrograman C++.

scholarly journals Hybridization of time synchronous averaging, singular value decomposition, and adaptive neuro fuzzy inference system for multi-fault bearing diagnosis

2020 ◽  
Vol 12 (12) ◽  
pp. 168781402098056
Author(s):  
Walid Touzout ◽  
Djamel Benazzouz ◽  
Fawzi Gougam ◽  
Adel Afia ◽  
Chemseddine Rahmoune
Keyword(s):  
Singular Value Decomposition ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Vibration Signal ◽  
Relevant Information ◽  
Singular Value ◽  
Inference System ◽  
Operation Conditions ◽  
Neuro Fuzzy ◽  
Value Decomposition

Bearing diagnosis has attracted considerable research interest; thus, researchers have developed several signal processing techniques using vibration analysis to monitor the rotating machinery’s conditions. In practical engineering, features extraction with most relevant information from experimental vibration signals under variable operation conditions is still regarded as the most critical concern. Therefore, actual works focus on combining Time Domain Features (TDFs) with decomposition techniques to obtain accurate results for defect detection, identification, and classification. In this paper, a new hybrid method is proposed, which is based on Time Synchronous Averaging (TSA), TDFs, and Singular Value Decomposition (SVD) for the feature extraction, then the Adaptive Neuro-Fuzzy Inference System (ANFIS) which gathers the advantages of both neural networks and fuzzy logic is applied for the classification process. First, TSA is used to reduce noises in the vibration signal by extracting the periodic waveforms from the disturbed data; thereafter, TDFs are applied on each synchronous signal to construct a feature matrix; afterwards, SVD is performed on the obtained matrices to remove the instability of statistical values and select the most stable vectors. Finally, ANFIS is implemented to provide a powerful automatic tool for features classification.

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. 

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