A method for hiding data in the spatial or IWT domains of images is proposed.Design new edge detection method to estimate same edge intensities for both images.XOR operation is used to embed the message and to improve imperceptibility.Proposed method is robust against textural feature steganalysis. In this paper, we present a novel image steganography algorithm that combines the strengths of edge detection and XOR coding, to conceal a secret message either in the spatial domain or an Integer Wavelet Transform (IWT) based transform domain of the cover image. Edge detection enables the identification of sharp edges in the cover image that when embedding in would cause less degradation to the image quality compared to embedding in a pre-specified set of pixels that do not differentiate between sharp and smooth areas. This is motivated by the fact that the human visual system (HVS) is less sensitive to changes in sharp contrast areas compared to uniform areas of the image. The edge detection method presented here is capable of estimating the exact edge intensities for both the cover and stego images (before and after embedding the message), which is essential when extracting the message. The XOR coding, on the other hand, is a simple, yet effective, process that helps in reducing differences between the cover and stego images. In order to embed three secret message bits, the algorithm requires four bits of the cover image, but due to the coding mechanism, no more than two of the four bits will be changed when producing the stego image. The proposed method utilizes the sharpest regions of the image first and then gradually moves to the less sharp regions. Experimental results demonstrate that the proposed method has achieved better imperceptibility results than other popular steganography methods. Furthermore, when applying a textural feature steganalytic algorithm to differentiate between cover and stego images produced using various embedding rates, the proposed method maintained a good level of security compared to other steganography methods.

A steganography embedding method based on edge identification and XOR coding

Digital watermarking is a technique for resolving copyright law in E-Commerce. In this article a combined watermarking method based on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) is proposed. For embedding watermark, a cover image is decomposed by a 2-level DWT, and the HL2 subband coefficients are divided into 4 × 4 blocks, then the DCT is performed on each of these blocks. The watermark bits are embedded by predefined pattern_0 or pattern_1 on the middle band coefficients of DCT. After inserting watermark, inverse DCT is applied to each 4 × 4 blocks of HL2 subband coefficients, and inverse DWT is applied to obtain the watermarked image. For watermark extraction, the watermarked image, which may be attacked by various image attacks, is decomposed with 2-level DWT and DCT similarly as watermark embedding process, then correlation between middle band coefficients of block DCT and the predefined pattern (pattern_0 and pattern_1) is calculated to decide whether a 0 bit or a 1...

An Improved Image Watermarking Method in Frequency Domain

The Digital Watermarking Technique has gained its importance due to its ability to provide the secure mechanism for copyright protection and authenticity of the digital data in this high growing internet and computer technology where the tampering and distribution of digital data illegally from unauthorized users is inevitable. For these two important properties of Digital Watermarking, i.e. Robustness and Imperceptibility of watermarked image must take into consideration. In this paper, invisible robust digital watermarking is proposed using Discrete Wavelet Transform and Singular Value Decomposition in YCbCr Color space. The performance of the proposed algorithm is compared with some previous works and results found are more robust against various geometric attacks.

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An Improved DWT-SVD Based Robust Digital Image Watermarking for Color Image

PSUM: Peer-to-peer multimedia content distribution using collusion-resistant fingerprinting

Steganography is a technology which is utilized in securing information through hiding data over another data which can be stored or passed over public network without a clue that secret data is hidden in the cover medium. This article focus on securing and hiding the data through transform domain techniques used in Image, Audio and Video steganography. The review study throws light on the algorithm and properties of transform domain techniques and its benefits to utilize in securing data. Parameters such as imperceptibility, capacity and robustness are evaluated for discrete cosine transform (DCT) and discrete wavelet transform (DWT). Key-words—Steganography; Discrete cosine transform; Discrete Fourier Transform; Discrete Wavelet Transform; Network security; Secure Communication Received: August 26, 2020 . Revised: November 16, 2020. Accepted: January 15, 2021. Published: January 22, 2021.

/pdf/securing-data-a-study-on-different-transform-domain-3curs7spvn.pdf

Securing Data: A Study on Different Transform Domain Techniques

In this paper a digital image watermarking based on 3 level discrete wavelet transform (DWT) is presented & compare it with 1 & 2 levels DWT. In this technique a multi-bit watermark is embedded into the low frequency sub-band of a cover image by using alpha blending technique. During embedding, watermark image is dispersed within the original image depending upon the scaling factor of alpha blending technique. Extraction of the watermark image is done by using same scaling factor as for embedding. Performance of method for different value of scaling factor is analyses & compare with 1& 2 levels DWT method by using statistical parameters such as peaksignal-to-noise-ratio (PSNR) and mean square error (MSE).Keywords: List four to six keywords which characterize the article. Key word— Image watermarking, 3 level DWT, Alpha Blending, MSE, PSNR

Pratibha Sharma

Papers

Digital Image Watermarking Using 3 level Discrete Wavelet Transform