An embedding strategy for large payload using convolutional embedding codes

A matrix embedding (ME) code is a commonly used steganographic technique that used linear block codes to perform the embedding process. However, a lack of low-complexity maximum-likelihood decoding schemes in linear block codes limited the embedding efficiency for sufficiently large lengths. This paper proposes a novel and practical hiding algorithm for binary data based on convolutional codes. Compared to a matrix embedding algorithm that uses linear block codes, the method proposed in this study is appropriate for embedding a sufficiently long message into a cover object. The proposed method employs the Viterbi decoding algorithm for embedding to identify the coset leader of convolutional codes for large payloads. Experimental results show that the embedding efficiency of the proposed scheme using convolutional codes is substantially superior to that of the scheme using linear block codes.