Embedding of any type of data in images based on a human visual model and multiple-based number conversion

A novel approach to embedding any type of digital data into a cover image is proposed, which utilizes a human visual model to guarantee that the modification of the cover image is imperceptible. A quantized contrast function based on the model is constructed first. The gray values of each 3×3 sub-image of the cover image are used to compute, using the function, a range of gray levels with the same contrast as that of the central pixel of the sub-image. The embedding process proceeds by replacing the gray value of the central pixel by one of the values in the range. This guarantees that the changes be imperceptible. The data to be embedded is treated as a binary stream and is partitioned into a number of sub-streams. A multiple-base number conversion mechanism is used to convert each sub-stream of data into values which are then embedded in the central pixels of sub-images. The embedded data can be extracted out from the resulting stego-image without referencing the original image. Experimental results show that the proposed method is feasible.