Novel Scheme for Data Hiding in Binary Images using Cover Pattern Histogram

In today’s digital age, security and safe communication are necessities. Applications frequently transport large amounts of private data as binary images. This research proposes a unique scheme that uses a cover pattern histogram-based decision tree for information concealment and extraction from binary images. This research aims to provide a data-hiding approach with a large capacity for data concealment, possible minor distortion, security, and difficulty discovering hidden data. This method uses high-frequency 3X3 pixel block patterns to obscure data. The two series of pattern’s are identified based on sorted block pattern frequency. To construct a decision tree for embedding, these series patterns, key bits, and information bits work together as parameters. Information is encrypted using a secret key to ensure message security before being hidden. A decision tree decides the block suitability and bit embedding with or without flipping at the sender side. A histogram of 3X3 pixel block patterns gets generated for the received image containing concealed data, and two series are recognized similarly to the embedding procedure at the receiver side. A decision tree assesses whether an image block carries an information bit and decides whether the bit is 0 or 1 . This decision tree extracts hidden data bits by analyzing series patterns and key bits. The secret key decodes retrieved concealed bits and reveal the original data. According to research, 50-80 % of hidden bits are transmitted without flipping the pixels, automatically reducing visual distortion. This scheme performs better than comparable methods and is applicable in steganography and watermarking.