Affiliations: [a]
ECE department, Karunya University, Coimbatore, India
| [b]
University of Oradea, Romania
| [c] Division of Data Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam | [d]
Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Abstract: Image steganography plays a vital role in hiding significant secret information within any input image. Numerous steganography techniques have been carried out to hide the secret information in images. In the current scenario, frequency domain techniques are widely preferred which are mostly transform based approaches. Conventionally, the secret data is hidden randomly in the coefficients of the transformed image. However, such random data hiding techniques lead to inferior performance of the overall system. Thus, using an optimization algorithm is obligatory to find out the optimal coefficients. Genetic Algorithm (GA) is normally used for selecting the optimal transform coefficients to enhance the system performance. However, conventional GA based approaches are highly random in nature which again leads to inaccurate results. In this work, a modified GA approach was proposed to determine the optimal coefficients in order to improve the embedding capacity and stego image quality. The achieved average peak signal to noise ratio (PSNR) was 50.29 dB with embedding capacity of 139361 bits. These experimental results validate the practical feasibility of the proposed methodology for image steganography.
Keywords: Fresnelet transform, frequency domain steganography, genetic algorithm, modified genetic algorithm, embedding capacity and peak signal to noise ratio
