Blind steganalysis based on features in fractional Fourier transform domain

Author

Zhou, Chao-En ; Feng, Jiu-chao ; Yang, Yi-Xian

Author_Institution

Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China

fYear

2009

fDate

23-25 July 2009

Firstpage

301

Lastpage

303

Abstract

Based on the good property of fractional Fourier transform (FRFT), two kinds of features of an image are extracted, i.e., the FRFT coefficients of image histogram and the histogram of image FRFT coefficients. Then, blind steganalysis is implemented to the features by using the support vector machine (SVM). The performance with respect to the two features is evaluated and compared by simulation. The results indicate that the classification performance is good, and the former is better than the latter.

Keywords

fast Fourier transforms; feature extraction; image classification; image coding; statistical analysis; steganography; support vector machines; watermarking; FRFT; SVM; blind steganalysis; classification performance; feature extraction; fractional Fourier transform domain; image histogram; information-hiding detection system; support vector machine; Chaos; Feature extraction; Fourier transforms; Frequency domain analysis; Histograms; Steganography; Support vector machine classification; Support vector machines; Switches; Wavelet domain;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Circuits and Systems, 2009. ICCCAS 2009. International Conference on

Conference_Location

Milpitas, CA

Print_ISBN

978-1-4244-4886-9

Electronic_ISBN

978-1-4244-4888-3

Type

conf

DOI

10.1109/ICCCAS.2009.5250507

Filename

5250507