On optimal feature selection using harmony search for image steganalysis

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.