A Novel Steganography Scheme Using Logistic Map, BRISK Descriptor, and K-Means Clustering

This paper introduces a novel steganography method for embedding and extracting a secret message from an image file using three stages. In the first stage, Binary Robust Invariant Scalable Keypoints (BRISK) and Good Features to Track are utilized to identify keypoints in the image. In the second stage, the k-means clustering algorithm is applied to these identified keypoints. The keypoints derived from the good features to track algorithm serve as cluster centers while the keypoints from the BRISK algorithm are distributed around these centers. In the last stage, the logistic map algorithm is employed to add more randomness to the obtained keypoints. This is done by distributing the points using the random list property. The results obtained indicate that the proposed method surpasses comparable techniques in terms of PSNR (Peak Signal-to-Noise Ratio), SSIM (Structural Similarity Index), and BER (Bit Error Rate) values metrics. Thus, the proposed scheme offers a performance advantage over existing methodologies.