Title :
Image Texture Energy-Entropy-Based Blind Steganalysis
Author :
Shuanghuan, Zhan ; Hongbin, Zhang
Abstract :
A novel approach of blind steganalysis is proposed, which is based on image texture energy-entropy features. Image complexity describes the difference of image´s content and texture. Steg-image´s texture is ordinarily more complicated than that of cover image. For analyzing image complexity, using image texture features to measure the statistical differences between cover image and steg-image. In the paper, we analyze image complexity based on image texture segmentation technique, and use Laws´ image texture energy-entropy features to measure the statistical differences between cover image and steg-image. Applying these texture features, blind steganalysis is implemented. Support Vector Machine (SVM) is used as classifier to distinguish whether a given image is embedded into the convert message. Experiment results show that the proposed approach is greatly valuable and our blind steganalysis method attains a good testing accurate rate.
Keywords :
Energy measurement; Image analysis; Image segmentation; Image texture; Image texture analysis; Statistics; Steganography; Support vector machine classification; Support vector machines; Testing; SVM; Steganography; blind steganalysis; image complexity; image texture segmentation; texture energy-entropy features;
Conference_Titel :
Signal Processing Systems, 2007 IEEE Workshop on
Conference_Location :
Shanghai, China
Print_ISBN :
978-1-4244-1222-8
Electronic_ISBN :
1520-6130
DOI :
10.1109/SIPS.2007.4387617