Abstract
In this paper, we propose a high-quality image authentication method based on absolute moment block truncation coding (AMBTC) compressed images. The existing AMBTC authentication methods may not be able to detect certain malicious tampering due to the way that the authentication codes are generated. In addition, these methods also suffer from their embedding technique, which limits the improvement of marked image quality. In our method, each block is classified as either a smooth block or a complex one based on its smoothness. To enhance the image quality, we toggle bits in bitmap of smooth block to generate a set of authentication codes. The pixel pair matching (PPM) technique is used to embed the code that causes the least error into the quantization values. To reduce the computation cost, we only use the original and flipped bitmaps to generate authentication codes for complex blocks, and select the one that causes the least error for embedment. The experimental results show that the proposed method not only obtains higher marked image quality but also achieves better detection performance compared with prior works.
Highlights
With the rapid development of the Internet, image editing softwares, such as Photoshop, Snapseed and Mix, have been rapidly developed
If the image is tampered during transmission, the authentication code embedded in the image will be changed
The authentication codes generated by [15,16,18] are independent of bitmaps or location information; these methods cannot detect tampering of bitmaps or swapping of image blocks
Summary
With the rapid development of the Internet, image editing softwares, such as Photoshop, Snapseed and Mix, have been rapidly developed. [16] proposes a method for AMBTC image authentication based on a special designed reference table, and this method outperforms previous works in terms of marked image quality Their approach does not utilize bitmaps to generate authentication codes, resulting in the inability to detect bitmap tampering. To obtain a better authentication effect and marked image quality, [18] uses quantized values of most significant bites (MSB) and bitmaps to generate authentication codes and embeds them into quantized values of least significant bits (LSB) Their method perturbs the MSB of the quantized values to reduce the error of embedding. They generate different authentication codes by toggling the bitmap and select the authentication code that causes the least error to embed into the quantized values Their method does not considered the flipped bitmap may result in a better embedding performance, limiting the image quality improvement.
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