Reversible audio data hiding algorithm using noncausal prediction of alterable orders

Abstract

This paper presents a reversible data hiding scheme for digital audio by using noncausal prediction of alterable orders. Firstly, the samples in a host signal are divided into the cross and the dot sets. Then, each sample in a set is estimated by using the past P samples and the future Q samples as prediction context. The order P + Q and the prediction coefficients are computed by referring to the minimum error power method. With the proposed predictor, the prediction errors can be efficiently reduced for different types of audio files. Comparing with the existing several state-of-the-art schemes, the proposed prediction model with expansion embedding technique introduces less embedding distortion for the same embedding capacity. The experiments on the standard audio files verify the effectiveness of the proposed method.

A Novel Robust Audio Watermarking Algorithm by Modifying the Average Amplitude in Transform Domain

“…Vivekananda [36] proposed a robust and blind audio watermarking algorithm based on SVD and QIM. Apart from the above algorithms, there are other audio watermarking algorithms in papers [4,7]. Wang [4] integrated exponent moments (EMs) and QIM to achieve an audio watermarking algorithm which used EMs to improve the robustness and QIM to realize the blind extraction of watermark, but this algorithm was not robust enough to resist amplitude scaling.…”

“…Wang [4] integrated exponent moments (EMs) and QIM to achieve an audio watermarking algorithm which used EMs to improve the robustness and QIM to realize the blind extraction of watermark, but this algorithm was not robust enough to resist amplitude scaling. Xiang [7] presented a reversible audio hiding scheme by using non-causal prediction. The scheme used the minimum error power method to calculate the optimum order and the prediction correlation of the audio data which could be used to embed the watermarks.…”

“…Perform DCT on De 1 (r, j) and De 2 (r, j) to obtain two transform-domain coefficients C 1 (r, j) and C 2 (r, j) with the length of N/2 r+1 , and then connect C 1 (r, j) and C 2 (r, j) to form an array C(r, n) with the length of N/2 r . Calculate the average amplitudes of |C(r, n)|, |C 1 (r, j)| and C 2 (r, j) according to Formulas (5)- (7).…”

“…Divide De (r) into the former packet De 1 (r, j) and the latter packet De 2 (r, j). Perform DCT on the two packets to obtain C 1 (r, j) and C 2 (r, j) and then calculate their average amplitudes respectively according to Formulas (6) and (7). If w(q) = 1, according to Formulas (6)-(9), the average amplitude of C 1 (r, j) is…”

“…Digital signature is a kind of number string which can be used as the secret key for both senders and receivers [5], and it easily stimulates the desire of illegal users to destroy the multimedia data. Digital watermarking technology conceals the watermarks into the multimedia data and later extracts such watermarks to prove the owner of multimedia data, so it is an efficient approach to protect the media contents, widely used for copyright protection, broadcast monitoring, fingerprinting, data authentication, and medical 2 of 17 safety, and it has become a hot topic in the field of communication and information security in recent years [6][7][8].…”