Anti-counterfeiting textured pattern.

Due to the proliferation of high-quality copying devices and the significant profits of counterfeit products, it is critical to establish an effective scheme for detecting and preventing the counterfeiting of goods. At present, most anti-faking schemes leave much to be desired in terms of cost, convenience, and ability to facilitate pre-sale authentication. The paper designs a unique textured pattern and proposes a triple anti-counterfeiting authentication (TACA). First, the textured pattern consists of triple encryptions (the first is that the key area of the QR code is covered, the second includes scale and Arnold transformation, and the third involves replacing the black areas of the pattern with random multi-level grayscales), the abundant details in the texture not only effectively conceal information, but also that their distortion will increase. Second, TACA comprises interpretability analysis (IA), spectral feature analysis (SFA), and spot matching analysis (SMA) in a cascaded way. In further detail, IA mainly exploits the positional transformation of individual pixels and the block features of local regions to restore interpretability. SFA uses the low-frequency subgraph of discrete wavelet transform (DWT) at a specified scale to capture macroscopic structural information. SMA is able to capture the detailed information of the pattern by utilizing SURF to detect the peak region rate positions and employing BRISK to accurately describe them before. Finally, this paper investigates the robustness of the proposed anti-counterfeiting scheme under a variety of copying methods (replicating, scanning-printing), capturing devices (smartphones), and attack scenarios (no attack, cropping, noise, blur). [ABSTRACT FROM AUTHOR]