Ammar Mohammadi

Ammar Mohammadi

This paper presents a reversible data hiding in encrypted image that employs based notions of the RDH in plain-image schemes including histogram modification and prediction-error computation. In the proposed method, original image may be encrypted by desire encryption algorithm. Most significant bit (MSB) of encrypted pixels are integrated to vacate room for embedding data bits. Integrated ones will be more resistant against failure of reconstruction if they are modified for embedding data bits. At the recipient, we employ chess-board predictor for lossless reconstruction of the original image by the aim of prediction-error analysis. Comparing to existent RDHEI algorithms, not only we propose a separable method to extract data bits, but also content-owner may attain a perfect reconstruction of the original image without having data hider key. Experimental results confirm that the proposed algorithm outperforms state of the art ones.

Ammar Mohammadi, Mansour Nakhkash

This paper presents a histogram based reversible data hiding (RDH) scheme, which divides image pixels into different cell frequency bands to sort them for data embedding. Data hiding is more efficient in lower cell frequency bands because it provides more accurate prediction. Using pixel existence probability in some pixels of ultra-low cell frequency band, another sorting is performed. Employing these two novel sorting methods in combination with the hiding intensity analysis that determines optimum prediction error, we improve the quality of the marked image especially for low embedding capacities. In effect, comparing to existent RDH algorithms, the hiding capacity is increased for a specific level of the distortion for the marked image. Experimental results confirm that the proposed algorithm outperforms state of the art ones.

Ammar Mohammadi, Mansor Nakhkash

This paper presents a reversible data hiding in encrypted image (RDHEI), which divides image into non-overlapping blocks. In each block, central pixel of the block is considered as leader pixel and others as follower ones. The prediction errors between the intensity of follower pixels and leader ones are calculated and analyzed to determine a feature for block embedding capacity. This feature indicates the amount of data that can be embedded in a block. Using this pre-process for whole blocks, we vacate rooms before the encryption of the original image to achieve high embedding capacity. Also, using the features of all blocks, embedded data is extracted and the original image is perfectly reconstructed at the decoding phase. In effect, comparing to existent RDHEI algorithms, embedding capacity is significantly increased in the proposed algorithm. Experimental results confirm that the proposed algorithm outperforms state of the art ones.