Steganalysis Using KL Transform and Radial Basis Neural Network
The essential problem in the security field is how to detect information hiding. This paper proposes a new steganalysis scheme based on artificial neural network as a classifier to detect information hiding in colored and grayscale images. The statistical features extracted from Karhunen-Loève (KL)...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Mosul University
2012-07-01
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| Series: | Al-Rafidain Journal of Computer Sciences and Mathematics |
| Subjects: | |
| Online Access: | https://csmj.mosuljournals.com/article_163670_da09ae23de117b261893e9548659de81.pdf |
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| Summary: | The essential problem in the security field is how to detect information hiding. This paper proposes a new steganalysis scheme based on artificial neural network as a classifier to detect information hiding in colored and grayscale images. The statistical features extracted from Karhunen-Loève (KL) transform coefficients obtained from co-occurrence matrix of image. Then radial basis neural network (RBNN) trained using these features to discriminate whether the image contains hidden information or not. This system can be used to prevent the suspicious secret communication. |
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| ISSN: | 1815-4816 2311-7990 |