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Image steganalysis using by high frequency Coefficients of Wavelet Windowing | ||
علوم و فناوریهای پدافند نوین | ||
Article 3, Volume 8, Issue 2 - Serial Number 28, May 2017, Pages 113-122 PDF (1.47 M) | ||
Author | ||
sobhan mousavi | ||
Receive Date: 30 January 2019, Revise Date: 17 July 2025, Accept Date: 30 January 2019 | ||
Abstract | ||
Steganalysis is one of the challenging and attractive subjects for the scientists interested in the development of steganography methods. Steganalysis is the procedure to detect the hidden information from the stego created by known steganography algorithms. Different kinds of extraction methods have been proposed for steganalysis, each have their own advantages when attacking different kinds of steganography methods. Making a combination of different feature sets will improve the performance of the steganalysis system. Most modern steganalysis algorithms train a supervised classifier on the feature vectors. One of the most popular and most accurate classifier is support vector machine (svm). In this paper, based on experiences and study different ways, an efficient steganalysis method using windowing on high-frequency coefficients of wavelet transform is proposed. In the proposed method, the final decision on the entire images is announced by majority voting technique using extracted convenient features of each window. Experimental and simulation results show that the proposed method for the detection message embedded in images, especially in low rates compared to existing steganalysis methods has more carefully hidden by about 99 percent. | ||
Keywords | ||
Wavelet Transform; Windowing; Cover; Classifier; Steganalysis; Stego Image | ||
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