OPTIMIZED DATA HIDING IN IMAGE STEGANOGRAPHY USING IMPROVED JAYA ALGORITHM

Image steganography gains popularity to secure secret data by hiding in the cover image. However, the data hiding process generates variability in the cover image. In order to reduce variability, various approaches have been proposed. Some of the authors are deployed swarm intelligence algorithms to search the optimal starting pixel in the cover image/best pixels in the cover image. On the other side, some authors match the secret data bits with the cover image bits, and the optimal index is determined. After that, hide the optimal index in the cover image using the LSB algorithm that generates the variability in it. In the proposed method, both approaches are hybridized. Initially, the cover image is read and it is split into two regions known as smooth and edge. The secret data bits match with the smooth region pixels and the optimal index is determined. After that, optimal indexes are hidden in the edge region using an improved JAYA algorithm to reduce the variability in the cover image. Besides that, pre-processing of the cover image is done based on the human visual characteristics to select the most appropriate planes for hiding the optimal indexes. The subjective and objective analysis is done for the proposed method to validate its performance. In the last, the proposed method is compared with the existing method based on the PSNR parameter.