Redundant Wavelet Watermarking using Spread Spectrum Modulation

Spread Spectrum modulation has become a preferred paradigm in many watermarking applications. This paper analyzes the performance of such a blind watermarking scheme under discrete wavelet frame rather than a traditional orthonormal wavelet expansion. The over complete representation offered by the redundant frame facilitates the identification of significant image features via a simple correlation operation across scales. The performance and resiliency of the proposed technique are analyzed against several volumetric distortion sources. The experimental results of this oblivious algorithm illustrate better visual and statistical imperceptibility and robustness compared to the usually critically sampled discrete wavelet transform. This algorithmic architecture utilizes the existing allocated bandwidth in the data transmission channel in a more efficient manner

Comparative Analysis of Techniques Used to Detect Copy-Move Tampering for Real-World Electronic Images

Evolution of high computational powerful computers, easy availability of several innovative editing software package and high-definition quality-based image capturing tools follows to effortless result in producing image forgery. Though, threats for security and misinterpretation of digital images and scenes have been observed to be happened since a long period and also a lot of research has been established in developing diverse techniques to authenticate the digital images. On the contrary, the research in this region is not limited to checking the validity of digital photos but also to exploring the specific signs of distortion or forgery. This analysis would not require additional prior information of intrinsic content of corresponding digital image or prior embedding of watermarks. In this paper, recent growth in the area of digital image tampering identification have been discussed along with benchmarking study has been shown with qualitative and quantitative results. With variety of methodologies and concepts, different applications of forgery detection have been discussed with corresponding outcomes especially using machine and deep learning methods in order to develop efficient automated forgery detection system. The future applications and development of advanced soft-computing based techniques in digital image forgery tampering has been discussed

Comparative Analysis of Techniques Used to Detect Copy-Move Tampering for Real-World Electronic Images

Evolution of high computational powerful computers, easy availability of several innovative editing software package and high-definition quality-based image capturing tools follows to effortless result in producing image forgery. Though, threats for security and misinterpretation of digital images and scenes have been observed to be happened since a long period and also a lot of research has been established in developing diverse techniques to authenticate the digital images. On the contrary, the research in this region is not limited to checking the validity of digital photos but also to exploring the specific signs of distortion or forgery. This analysis would not require additional prior information of intrinsic content of corresponding digital image or prior embedding of watermarks. In this paper, recent growth in the area of digital image tampering identification have been discussed along with benchmarking study has been shown with qualitative and quantitative results. With variety of methodologies and concepts, different applications of forgery detection have been discussed with corresponding outcomes especially using machine and deep learning methods in order to develop efficient automated forgery detection system. The future applications and development of advanced soft-computing based techniques in digital image forgery tampering has been discussed

Comparison of DCT, SVD and BFOA based multimodal biometric watermarking systems

AbstractDigital image watermarking is a major domain for hiding the biometric information, in which the watermark data are made to be concealed inside a host image imposing imperceptible change in the picture. Due to the advance in digital image watermarking, the majority of research aims to make a reliable improvement in robustness to prevent the attack. The reversible invisible watermarking scheme is used for fingerprint and iris multimodal biometric system. A novel approach is used for fusing different biometric modalities. Individual unique modalities of fingerprint and iris biometric are extracted and fused using different fusion techniques. The performance of different fusion techniques is evaluated and the Discrete Wavelet Transform fusion method is identified as the best. Then the best fused biometric template is watermarked into a cover image. The various watermarking techniques such as the Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD) and Bacterial Foraging Optimization Algorithm (BFOA) are implemented to the fused biometric feature image. Performance of watermarking systems is compared using different metrics. It is found that the watermarked images are found robust over different attacks and they are able to reverse the biometric template for Bacterial Foraging Optimization Algorithm (BFOA) watermarking technique

ANALISIS AUDIO WATERMARKING BERBASIS STATIONARY WAVELET TRANSFORMATION DENGAN METODE PENYISIPAN SPREAD SPECTRUM DAN DIOPTIMASI ALGORITMA GENETIKA

Kita telah memasuki era dimana informasi bisa disebarluaskan dalam bentuk digital. Berbagai macam informasi entah itu dalam bentuk teks, audio, citra, maupun audio kini dapat dengan mudah diunggah dan diakses oleh berbagai kalangan dengan cepat dan mudah. Namun juga tidak sedikit oknum yang menyalahgunakan kelebihan ini untuk kepentingannya sendiri, tidak terkecuali file dalam bentuk audio yang akan dibahas pada tugas akhir ini. Audio menjadi salah satu bentuk file yang paling banyak dilanggar hak ciptanya, seperti proses pengambilan sebagian (resampling) sebagai contoh yang paling umum. Karena itu, tugas akhir ini memberikan solusi agar dapat mencegah terjadinya pelanggaran tersebut, dengan menggunakan metode watermarking. Watermarking adalah proses penyisipan file sebagai tanda atau copyright tanpa merusak file aslinya. File yang disisipkan pada tugas akhir ini berupa citra dengan audio sebagai file host. Metode yang akan digunakan pada tugas akhir ini antara lain Stationary Wavelet Transformation (SWT), dengan metode penyisipan Spread Spectrum (SS), dan dioptimasi menggunakan algoritma genetika. SWT merupakan modifikasi dari metode yang sudah lebih umum diketahui yaitu Discrete Wavelet Transformation (DWT). Yang membedakan keduanya adalah tidak adanya proses downsampling pada SWT setelah dilakukan proses dekomposisi. Spread Spectrum adalah metode penyisipan dengan hasil dimana watermark akan disisipkan pada frekuensi rendah sehingga lebih sulit untuk dideteksi. Algoritma genetika digunakan untuk menentukan parameter evaluasi kualitas yang akan dimodifikasi sehingga data watermark masih memiliki imperceptibility dan robustness yang baik. Diimplementasikan menggunakan MATLAB, audio akan diuji dengan dua macam serangan yaitu resampling, dan kompresi MP3. Setalah dilakukan pengujian akan dilanjutkan dengan optimasi menggunakan Algen. Dari pengujian tersebut akan didapatkan parameter keluaran dari masing-masing lima jenis audio dengan diberikan dua macam serangan tersebut. Dari proses tersebut akan didapatkan parameter keluaran, yaitu ODG, SNR, BER dan C

Lifting dual tree complex wavelets transform

We describe the lifting dual tree complex wavelet transform (LDTCWT), a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). We describe a way to estimate the accuracy of this approximation and style appropriate filters to attain this. These benefits are often exploited among applications like denoising, segmentation, image fusion and compression. The results of applications shrinkage denoising demonstrate objective and subjective enhancements over the dual tree complex wavelet transform (DTCWT). The results of the shrinkage denoising example application indicate empirical and subjective enhancements over the DTCWT. The new transform with the DTCWT provide a trade-off between denoising computational competence of performance, and memory necessities. We tend to use the PSNR (peak signal to noise ratio) alongside the structural similarity index measure (SSIM) and the SSIM map to estimate denoised image quality

A High Payload Steganography Mechanism Based on Wavelet Packet Transformation and Neutrosophic Set

In this paper a steganographic method is proposed to improve the capacity of the hidden secret data and to provide an imperceptible stego-image quality. The proposed steganography algorithm is based on the wavelet packet decomposition (WPD) and neutrosophic set. First, an original image is decomposed into wavelet packet coefficients. Second, the generalized parent-child relationships of spatial orientation trees for wavelet packet decomposition are established among the wavelet packet subbands. An edge detector based on the neutrosophic set named (NSED) is then introduced and applied on a number of subbands. This leads to classify each wavelet packet tree into edge/non-edge tree to embed more secret bits into the coefficients in the edge tree than those in the non-edge tree. The embedding is done based on the least significant bit substitution scheme. Experimental results demonstrate that the proposed method achieves higher embedding capacity with better imperceptibility compared to the published steganographic methods