Name
Abstract | ||
|---|---|---|
The purpose of image steganalysis is to detect the presence of hidden messages in cover images. Steganalysis can be considered as a pattern recognition process to decide which class a test image belongs to: the cover photographic images or the stego-image. We present harmony search algorithm for feature selection for image steganalysis. Experiment show that the proposed hybrid algorithm for feature selection increases the testing accuracy of classifying result. The combination of the feature set extracted is likely to improve the performance of general steganalysis methods which have more real value for deterring covert communications and the uncorrelated features extracted contain more discriminatory information when distinguish different kinds of steganography. © 2012 IEEE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICNC.2012.6234730 | ICNC |
Keywords | Field | DocType |
feature selection,harmony search,steganalysis,hybrid algorithm,support vector machines,feature extraction,accuracy,genetic algorithms,optimization,classification algorithms,steganography,pattern recognition,test image,harmony search algorithm | Feature selection,Feature detection (computer vision),Computer science,Artificial intelligence,Standard test image,Steganography,Computer vision,Pattern recognition,Feature (computer vision),Feature extraction,Harmony search,Steganalysis,Machine learning | Conference |
Volume | Issue | Citations |
null | null | 1 |
PageRank | References | Authors |
0.36 | 8 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guo-ming Chen | 1 | 3 | 2.07 |
| Dong Zhang | 2 | 3 | 1.06 |
| Wei-Heng Zhu | 3 | 2 | 3.17 |
| Qian Tao | 4 | 59 | 14.00 |
| Chaoxia Zhang | 5 | 20 | 3.51 |
| Jinxin Ruan | 6 | 2 | 0.72 |