Abstract
The image-based data hiding method is a technology used to transmit confidential information secretly. Since images (e.g., grayscale images) usually have sufficient redundancy information, they are a very suitable medium for hiding data. Absolute Moment Block Truncation Coding (AMBTC) is one of several compression methods and is appropriate for embedding data due to its very low complexity and acceptable distortion. However, since there is not enough redundant data compared to grayscale images, the research to embed data in the compressed image is a very challenging topic. That is the motivation and challenge of this research. Meanwhile, the Hamming codes are used to embed secret bits, as well as a block code that can detect up to two simultaneous bit errors and correct single bit errors. In this paper, we propose an effective data hiding method for two quantization levels of each block of AMBTC using Hamming codes. Bai and Chang introduced a method of applying Hamming (7,4) to two quantization levels; however, the scheme is ineffective, and the image distortion error is relatively large. To solve the problem with the image distortion errors, this paper introduces a way of optimizing codewords and reducing pixel distortion by utilizing Hamming (7,4) and lookup tables. In the experiments, when concealing 150,000 bits in the Lena image, the averages of the Normalized Cross-Correlation (NCC) and Mean-Squared Error (MSE) of our proposed method were 0.9952 and 37.9460, respectively, which were the highest. The sufficient experiments confirmed that the performance of the proposed method is satisfactory in terms of image embedding capacity and quality.
Highlights
The Internet space has become like a single trading world where almost all digital content is distributed because every trading system is connected by high speed Internet, such as 5G.Many people distribute digital content in this space and are constantly consuming digital content.The problem with this digital space is that a copyright protection problem occurs because digital content is redistributed, copied, and modified by illegal users
We introduce a general framework for Data Hiding (DH) based on Absolute Moment Block Truncation Coding (AMBTC) with the minimal squared error by the optimal Hamming code using a Lookup Table (LUT)
The DH capacity is the size of the secret bit that is embedded in the cover image
Summary
The Internet space has become like a single trading world where almost all digital content is distributed because every trading system is connected by high speed Internet, such as 5G. Chuang and Chang [28] proposed a DH method based on AMBTC replacing the bitmaps of smooth blocks with the secret bits after dividing the blocks of an image into smooth blocks and complex blocks directly. Ou and Sun [29] introduced a way to embed data in the bitmaps of smooth blocks and proposed a method to reduce the distortions of the image by adjusting two quantization levels through re-computation, but the original image is required for re-calculation. In 2017, Huang et al [35] proposed a scheme for hiding data using pixel differences (hidden bits = log T: derived from the difference expansion method) at two quantization levels and introduced a method to adjust the differences in the quantization levels to maintain image quality This method is a hybrid method by using OTQL and DBS as well.
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