Image Steganography Approach Based Ant Colony Optimization with Triangular Chaotic Map

To establish the secure communication using image steganography by hiding the information in cover image, the study focus on image steganography based on Ant Colony Optimization (ACO) where the cover image is divided into number of 5×5 blocks. As pixel values after ACO are considered as the optimal pixels, the ants search the next qualified pixels on reference to pheromone trails to encode the text messages. After ACO, Triangular Chaotic Map (TCM) is imposed based on initial value of chaotic sequences. The proposed method outperformed other state-of-art methods like classical Least Significant Bit(LSB), LSB with ACO, LSB with logistic map for all the images under consideration: lenna.png (0.00046, 83.4021, 0.0007, 0.9990964, 0.9983), baboon.png (0.00027, 82.5526, 0.0009, 0.9990542, 0.9985), pepper.png (0.00067, 71.2322, 0.0004, 0.9990560, 0.9947), dog.png (0.00045, 70.4590, 0.0005, 0.9990024, 0.9904) and flower.png (0.00067, 71.2322, 0.0004, 0.9990560, 0.9947) under the evaluation metrics as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), F-Score and Structural Similarity Index Matrix (SSIM) respectively.