IMAGE STEGANALYSIS BASED ON FEATURES OF CO-OCCURRENCE MATRIX

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ABO ALGHASEMI MOJTABA; AGHAEINIA H.; FAEZ K.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS Year:2010 | Volume:7 | Issue:1 Page(s): 15-24

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,273

Download:

Cites:

Information Journal Paper

Title

IMAGE STEGANALYSIS BASED ON FEATURES OF CO-OCCURRENCE MATRIX

Author(s)

ABO ALGHASEMI MOJTABA | AGHAEINIA H. | FAEZ K. | Issue Writer Certificate

Keywords

STEREOPHONIC ACOUSTIC ECHOQ2

ADAPTIVE FILTERQ2

CONVERGENCE RATEQ3

MISALIGNMENTQ3

CROSS-CORRELATIONQ3

CENTER-CLIPPINGQ3

Abstract

In this paper two novel steganalysis methods is presented based on co-occurrence matrix of an image. It is shown that by using features extracted from this matrix, we can differentiate between cover and stego images. These features include energy, entropy, contrast, inverse difference moment, maximum probability and correlation. We use SVM classification for separation of cover and stego images. In the second method, we directly use the diagonal elements of co-occurrence matrix as a feature and we remove some bit planes of an image for feature dimension reduction. Experiments on the 1800 images for LSB and LSB matching (LSBM) algorithms are performed with different rates for the same database. By comparing the results, we also show that the detection rates effectively are increased with respect to previous steganalysis techniques.

Cites

A LARGE SCALE IMAGE INPAINTING METHOD BASED ON IMAGE DECOMPOSITION TO TEXTURE AND STRUCTURE SUB-IMAGES

References

Cite

APA: Copy

ABO ALGHASEMI, MOJTABA, AGHAEINIA, H., & FAEZ, K.. (2010). IMAGE STEGANALYSIS BASED ON FEATURES OF CO-OCCURRENCE MATRIX. JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS, 7(1), 15-24. SID. https://sid.ir/paper/115763/en

Vancouver: Copy

ABO ALGHASEMI MOJTABA, AGHAEINIA H., FAEZ K.. IMAGE STEGANALYSIS BASED ON FEATURES OF CO-OCCURRENCE MATRIX. JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS[Internet]. 2010;7(1):15-24. Available from: https://sid.ir/paper/115763/en

IEEE: Copy

MOJTABA ABO ALGHASEMI, H. AGHAEINIA, and K. FAEZ, “IMAGE STEGANALYSIS BASED ON FEATURES OF CO-OCCURRENCE MATRIX,” JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS, vol. 7, no. 1, pp. 15–24, 2010, [Online]. Available: https://sid.ir/paper/115763/en

Related Journal Papers