Performance comparison of DCT and Walsh transform for steganography

Kekre, H. B.; Athawale, Archana; Halarnkar, Pallavi N.; Banura, Varun K.

doi:10.1145/1741906.1741921

Cited by 15 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results indicate the feasibility of the proposed approach although the computational requirements are significant. The results correspond with parts of [19], [20] and are also somewhat inferior to those achieved using hybrid wavelet transforms on images but illustrate the feasibility of the application of wavelets for video steganography.…”

Section: Discussionmentioning

confidence: 60%

Wavelet Based Color Video Steganography

Kolakalur¹,

Kagalidis²,

Vuksanović³

2016

IJET

View full text Add to dashboard Cite

Abstract-This paper describes the algorithm developed with the aim to hide a "secret" color video sequence within another color video sequence. An approach to apply a wavelet transform in order to decompose the cover video sequence and then replace the less significant wavelet band with "secret" video frames has been implemented and tested. On the receiver side, process is reversed and the hidden color video recovered from stego color video. Proposed algorithm has been implemented using Mat lab and PSNR and MSE error metrics employed to evaluate the quality of both video sequences.Index Terms-Discrete wavelets transform (DWT), LSB, PSNR, and Steganography.

show abstract

Section: Discussionmentioning

confidence: 60%

Wavelet Based Color Video Steganography

Kolakalur¹,

Kagalidis²,

Vuksanović³

2016

IJET

View full text Add to dashboard Cite

show abstract

“…The first type algorithms pay more attention to embedding capacity, such as those proposed by [11][12][13], the second type algorithms are absorbed in robustness, such as those proposed by [15][16][17][18]22], and the third type algorithms emphasize a compromise of capacity, robustness, and invisibility, such as those in [19][20][21]. It cannot say that the capacity of our proposed algorithm is as good as the first type and the robustness is as good as the second type because it belongs to the third type.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…The hiding algorithm based on LSB proposed by [12,14] that based on MSB in [13] and that based on de-clustering in [11], all have large capacity, but the robustness is not satisfactory. The hiding algorithm based on DWT in [15] and those based on discrete cosine transform (DCT) in [16][17][18] have good robustness and good invisibility; however, the data hiding capacity is very low because it is not originally designed for this purpose of large amount. It has become a hot spot on how to balance the invisibility, robustness, and capacity of the hiding algorithm.…”

Section: Motivationmentioning

confidence: 99%

An image information hiding algorithm based on grey system theory

Huang

Chen

et al. 2013

Int J Communication

View full text Add to dashboard Cite

SUMMARYOn the basis of grey system theory, an image information hiding algorithm is proposed in this paper. First, to choose the blocks of rich texture, a method based on two-dimensional grey relational analysis is designed; making use of the improved GM(1,1) prediction model, the secret image is compressed losslessly, and then scrambled by means of time-division multiplexing method in communication theory. Block discrete cosine transform is applied to the chosen blocks, and coefficients of mid frequencies are chosen as the embedded data, whereas the embedding intensity is determined on the basis of human visual system, and the embedding capacity of sub-blocks can be controlled by its two-dimensional grey relational grade adaptively. The experiment results show that the algorithm cannot only achieve satisfactory invisibility and robustness, but also improve the payload of the cover image, and meanwhile solve the problem that the small capacity of traditional algorithms in transform domain efficiently. Copyright © 2013 John Wiley & Sons, Ltd. , which takes the uncertain, little sample, poor information system as the research object, presented by Chinese scholar Julong Deng as an emerging discipline. Its contents mainly include grey prediction model, grey relational analysis, grey decision-making, and so forth. Information hiding technology is one of its important applied fields [2,3].Information hiding model was derived from 'prisoners problem', put forward by Simmons in 1984. To deliver information secretly, traditional cryptography [4, 5] mainly use replacing or scrambling technologies to disrupt the original features of the secret information. Just because cipher texts resemble a stream of meaningless codes, they easily attract attacker to try to either recover them or simply destroy them, which seriously affect the security of information communication. To circumvent this problem, information hiding technology [6-8] mainly focus on how to hide the coded information into another host media, which makes it hard for attackers to find out the secret information. And, it is also impossible to detect the carrier from vast amounts of data in communication channel. These characteristics make it widely accepted in information security fields.[9] provides one efficient means of concealing the authentication messages exchanged

show abstract

“…So they can be "mixed up" using actions of reversing multiplying, summing which is also called as convolution. These wavelets are becoming very useful for huge number of applications like fingerprint application, palm print application, Steganography [2], Iris recognition. The wavelets exploited largely and also grow to be important in the fields of image compression, analyses of Electrocardiogram (ECG), Deoxyribonucleic Acid (DNA), Face and speech recognition, computer graphics.…”

Section: Introductionmentioning

confidence: 99%

Quality Improvement in Color Image Compression using New FDCT and FIDCT

Mary¹,

Ramachandran²

2015

IJCA

View full text Add to dashboard Cite

The image compression methods aim to compress color image while ensuring that noise removal compression technique produce the good quality level images. The storage of images is becoming difficult with number of images growing to million and billions. Hence the image compression becoming absolute necessity in computing field. The Discrete Cosine Transform is widely used in image compression technique. Redundant information in an image needs to be eliminated by adopting intelligent method. In the recent research attempts better quality of compression is observed with the use of Discrete Cosine Transform (DCT) and Quantization. In this paper, the proposed system efficient image encoder removes the sinusoidal noise from original image by Butterworth Band Reject Filter (BBRF) algorithm in FDCT color image compression. The objective of this color image compression scheme is efficiently noise removal image, calculate the Compression Ratio(CR), Peak Signal to Noise Ratio (PSNR) Mean Square Error (MSE) by changing the FDCT level and using Fine Inverse Discrete Cosine Transform (F-IDCT) factor while preserving the quality of reconstructed image. Experimentation has been carried out on different image formats successfully. The proposed system achieved a good compression ratio and considerable test application for the quality of the reconstructed color image.

show abstract

Performance comparison of DCT and Walsh transform for steganography

Cited by 15 publications

References 16 publications

Wavelet Based Color Video Steganography

Wavelet Based Color Video Steganography

An image information hiding algorithm based on grey system theory

Quality Improvement in Color Image Compression using New FDCT and FIDCT

Contact Info

Product

Resources

About