Enhancing Steganography Cover Selection: A Strategic Approach using Image Texture Complexity Analysis

This paper presents an innovative framework for enhancing data hiding in image steganography through strategic cover selection techniques. With the increasing need for secure data exchange, steganography offers a promising solution by embedding information imperceptibly within cover images. However, the success of this method relies heavily on the appropriate selection of cover images. To address this, we introduce an efficient cover selection method using Image Texture (ImTex) complexity analysis. This approach involves setting threshold values for various image properties to emphasize the selection of optimal cover images. Our experiments demonstrate that this strategic approach significantly improves embedding capacity, data security, and imperceptibility, while maintaining high visual quality. By making the source code and datasets openly available, we aim to facilitate further research and applications in the field of image steganography.