22 research outputs found
Digital Image Steganography Based On Integer Haar Wavelet Transform And Coefficient Difference
The development of digital information led to the demand for information security technology that protects the confidentiality of information. Digital steganography is one of such technology that able to protect the information from illegal interception due to its capability to hide the existence of the information without attracting the eavesdropper‟s attention. Among digital media, digital image is the most widely used media for steganography. Discrete Cosine Transform (DCT) is a well-known technique in digital image steganography, but the block calculation of DCT may pose artifact on the images. The disadvantages of DCT can be eliminating by the Discrete Wavelet Transform (DWT) which is more compatible with the Human Visual System (HVS). However the floating point of DWT can causes loss of information. On the other hand, Integer Wavelet Transform (IWT) is represented in finite precision numbers, which can avoid the problem of floating point precision of DWT. In this study, the messages are embedded on the wavelet coefficients of 1-level Integer Haar Wavelet Transform (IHWT) using Coefficient Difference scheme that adopted from Pixel Value Differencing (PVD). The messages are embedded on the difference value of two adjacent wavelet coefficients. Peak Signal to Noise Ration (PSNR) and Structural Similarity (SSIM) are used to measure the quality of stego image. The result shows that the proposed method has outperformed the existing method that employ IHWT and Pixel Mapping Method (PMM) in term of capacity vs. imperceptibility, as well as the maximum capacity. This is due to the high degree of Coefficient Difference that can tolerate larger modification of wavelet coefficients. Moreover, the Coefficient Difference can be applied on all coefficients instead of either significant or insignificant coefficient. These lead to the both high capacity and imperceptibility of digital image steganography system
A Novel Watermarking Method using Hadamard Matrix Quantization
One of the most used watermarking algorithms is Singular Value Decomposition (SVD), which has a balanced level of imperceptibility and robustness. However, SVD uses a singular matrix for embedding and two orthogonal matrices for reconstruction, which is inefficient. In this paper, a Hadamard matrix is used to get a singular matrix for the reconstruction process. Moreover, SVD works with a floating-point value, which takes long processing time, while the Hadamard matrix works with an integer range, which is more efficient. Visual measurement showed that SVD and the new method had average NC values of 0.8321 and 0.8293, whereas the average SSIM values resulted in the same value (0.9925). In terms of processing time, the proposed method ran faster than SVD with an embedding and extraction time of 0.6308 and 0.2163 seconds against 0.8419 and 0.2935 seconds. The proposed method successfully reduced the running time while maintaining imperceptibility and robustness
ROBUST INTEGER HAAR WAVELET BASED WATERMARKING USING SINGULAR VALUE DECOMPOSITION
This paper proposed a hybrid watermarking method that used dither quantization of Singular Value Decomposition (SVD) on average coefficients of Integer Haar Wavelet Transform (IHWT). The watermark image embeds through dither quantization process on singular coefficients value. This scheme aims to obtain the higher robustness level than previous method which performs dither quantization of SVD directly on image pixels value. The experiment results show that the proposed method has proper watermarked images quality above 38dB. The proposed method has better performance than the previous method in term of robustness against several image processing attacks. In JPEG compression with Quality Factor of 50 and 70, JPEG2000 compression with Compression Ratio of 5 and 3, average filtering, and Gaussian filtering, the previous method has average Normalized Correlation (NC) values of 0.8756, 0.9759, 0.9509, 0.9905, 0.8321, and 0.9297 respectively. While, the proposed method has better average NC values of 0.9730, 0.9884, 0.9844, 0.9963, 0.9020, and 0.9590 respectively
Fragile watermarking for image authentication using dyadic walsh ordering
A digital image is subjected to the most manipulation. This is driven by the easy manipulating process through image editing software which is growing rapidly. These problems can be solved through the watermarking model as an active authentication system for the image. One of the most popular methods is Singular Value Decomposition (SVD) which has good imperceptibility and detection capabilities. Nevertheless, SVD has high complexity and can only utilize one singular matrix S, and ignore two orthogonal matrices. This paper proposes the use of the Walsh matrix with dyadic ordering to generate a new S matrix without the orthogonal matrices. The experimental results showed that the proposed method was able to reduce computational time by 22% and 13% compared to the SVD-based method and similar methods based on the Hadamard matrix respectively. This research can be used as a reference to speed up the computing time of the watermarking methods without compromising the level of imperceptibility and authentication
Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem
CRT was a widely used algorithm in the development of watermarking methods. The algorithm produced good image quality but it had low robustness against compression and filtering. This paper proposed a new watermarking scheme through dual band IWT to improve the robustness and preserving the image quality. The high frequency sub band was used to index the embedding location on the low frequency sub band. In robustness test, the CRT method resulted average NC value of 0.7129, 0.4846, and 0.6768 while the proposed method had higher NC value of 0.7902, 0.7473, and 0.8163 in corresponding Gaussian filter, JPEG, and JPEG2000 compression test. Meanwhile the both CRT and proposed method had similar average SSIM value of 0.9979 and 0.9960 respectively in term of image quality. The result showed that the proposed method was able to improve the robustness and maintaining the image quality
Imperceptible Image Watermarking based on Chinese Remainder Theorem over the Edges
This paper introduced a watermarking method using the CRT and Canny Algorithm that able to improve the imperceptibility of watermarked image and preserving the robustness of watermark image as well. The classical CRT algorithm is spread the watermark bits evenly on the image area. It causes significant degradation when the embedding location lies on the least significant region or in the homogeny area. Otherwise, the proposed method embeds the watermark on the edges of the image which have significant difference value to maintain the imperceptibility. The Canny algorithm is used to indexing the embedding location based on the filtering output of host image. The watermark is then embedded into the host image using pair-wise coprime integers of 6 and 11 within the CRT modulo. The results show that the proposed method has significant improvement in the quality of watermarked image with the average value of 0.9995 compared to the CRT method which results in value of 0.9985. In compression and additive noise attacks the CRT has average values of 0.6618 and 0.9750, while the proposed method results in similar values of 0.6616 and 0.9752 respectively. These prove that the proposed method is able to preserve the robustness while improving the imperceptibility
Face Recognition based on CNN 2D-3D Reconstruction using Shape and Texture Vectors Combining
This study proposes a face recognition model using a combination of shape and texture vectors that are used to produce new face images on 2D-3D reconstruction images. The reconstruction process to produce 3D face images is carried out using the convolutional neural network (CNN) method on 2D face images. Merging shapes and textures vector is used to produce correlation points on new face images that have similarities to the initial image used. Principal Component Analysis (PCA) is used as a feature extraction method, for the classification method we use the Mahalanobis method. The results of the tests can produce a better recognition rate compared to face recognition testing using 2D images
Robust Digital Image Steganography Within Coefficient Difference On Integer Haar Wavelet Transform
The development of digital information has lead to increasing demands on information security technology in order to protect the confidentiality of information. Digital steganography is one of technologies that is capable of protecting the information from unauthorized interception. It is due to its capability to hide the embedded of the information without attracting the eavesdropper’s attention. Among digital media, digital image is the most widely used medium for steganography. Discrete Cosine Transform (DCT) is a well known technique in digital image steganography. The use of DCT on small blocks may pose blocking effects and unintended artifacts on the overall image. These disadvantages of DCT can be eliminated by using Discrete Wavelet Transform (DWT) which is more compatible with the Human Visual System (HVS). However the floating point of DWT can causes some loss of information. On the other hand, Integer Wavelet Transform (IWT) represented in finite precision can avoid the problem of floating point precision in DWT. In this paper, the messages are embedded on the 1-level Integer Haar Wavelet Transform (IHWT) using coefficient difference scheme that is adopted from Pixel Value Differencing (PVD). The messages are embedded on the difference values of two adjacent wavelet coefficients. The result shows that the proposed method can easily outperform the existing method that employ IHWT and Pixel Mapping Method (PMM) in term of imperceptibility as well as the maximum capacity
Feature Image Watermarking Based on Bicubic Interpolation of Wavelet Coefficients Using CRT
The main objective of watermarking method is to improve the robustness and imperceptibility. This paper introduces an improved CRT watermarking method using absolute value of interpolated wavelet coefficients aiming to improve the imperceptibility and robustness. The standard CRT method embeds the watermark bits on the blocks of pixels evenly. Hence, it can significantly reduce the quality of watermarked images when the watermark lies on the homogeneous area. Otherwise, the proposed method is embedding the watermark bits on the heterogeneous area by sorting the absolute magnitude of wavelet coefficients descending. The wavelet
coefficients are selected from high frequency wavelet sub band HH. This scheme is able to determine the appropriate embedding location in certain range of value. The watermark bits are then embedding on the selected
pixel value using CRT scheme. The result shows that the average imperceptibility value the CRT is 0.9980 while the proposed method has average value of 0.9993. On robustness against compression, the proposed method achieves better result compared to the CRT with the average NC values of 0.7916 higher than the CRT value of 0.7530. These prove that the proposed method has better performance in term of imperceptibility and robustness against compression than the CRT method