| Title | Robust data retrieval from high-security structural colour QR codes via histogram equalization and decorrelation stretching |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Abdolahi, Mahssa, Jiang, Hao, Kaminska, Bozena |
| Conference Name | 2019 IEEE 10th Annual Ubiquitous Computing, Electronics Mobile Communication Conference (UEMCON) |
| Keywords | blue channels, blue periodicities, cross-channel interference effects, cryptography, cyber physical systems, data readout, data recovery, Data storage systems, decoded structural colour QR codes, decorrelation stretching, diffraction grating equation, diffraction gratings, Diffractive nano-optics, document security, generic diffractive RGB-pixelated periodic nanocones, green channels, green periodicities, high-security structural colour QR codes, histogram equalization, image colour analysis, image denoising, image enhancement, image sensors, information retrieval, interpolation, lighting conditions, linear spatial low-pass mean filtering, multiple image processing techniques, pubcrawl, QR Code decoding, QR codes, red channels, red periodicities, Resiliency, robust data retrieval, security of data, Structural colour QR codes |
| Abstract | In this work, robust readout of the data (232 English characters) stored in high-security structural colour QR codes, was achieved by using multiple image processing techniques, specifically, histogram equalization and decorrelation stretching. The decoded structural colour QR codes are generic diffractive RGB-pixelated periodic nanocones selectively activated by laser exposure to obtain the particular design of interest. The samples were imaged according to the criteria determined by the diffraction grating equation for the lighting and viewing angles given the red, green, and blue periodicities of the grating. However, illumination variations all through the samples, cross-module and cross-channel interference effects result in acquiring images with dissimilar lighting conditions which cannot be directly retrieved by the decoding script and need significant preprocessing. According to the intensity plots, even if the intensity values are very close (above 200) at some typical regions of the images with different lighting conditions, their inconsistencies (below 100) at the pixels of one representative region may lead to the requirement for using different methods for recovering the data from all red, green, and blue channels. In many cases, a successful data readout could be achieved by downscaling the images to 300-pixel dimensions (along with bilinear interpolation resampling), histogram equalization (HE), linear spatial low-pass mean filtering, and gamma function, each used either independently or with other complementary processes. The majority of images, however, could be fully decoded using decorrelation stretching (DS) either as a standalone or combinational process for obtaining a more distinctive colour definition. |
| DOI | 10.1109/UEMCON47517.2019.8993032 |
| Citation Key | abdolahi_robust_2019 |
Robust data retrieval from high-security structural colour QR codes via histogram equalization and decorrelation stretching