降低特征类内离散度的JPEG图像隐写分析

doi:10.3969/j.issn.0255-8297.2019.01.005

Abstract

Abstract:

Compared with the process of embedding, image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger within-class scatter distances and smaller between-class scatter distances. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are classified according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close complexity evaluation function to build a classifier. The theoretical analysis and experimental results can demonstrate the validity of the proposed framework.

Key words: steganalysis, between-class scatter, image classification, image content complexity

CLC Number:

TP391

WANG Ran, NIU Shao-zhang, PING Xi-jian, ZHANG Tao, SANG Xiao-dan. Steganalysis of JPEG Images Based on Reducing Between-Class Scatter[J]. Journal of Applied Sciences, 2019, 37(1): 41-50.

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Steganalysis of JPEG Images Based on Reducing Between-Class Scatter

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