Improved color barcodes via Expectation Maximization style interference cancellation
Encoding data independently in cyan, magenta, and yellow (CMY) print colorant channels with detection in complementary Red, green, and blue (RGB) image capture channels offers an attractive framework for extending monochrome barcodes to color with increased data rates. The undesired absorption of colorants in regions of spectral sensitivity of the noncomplementary capture channels, however, gives rise to cross-channel color interference that significantly deteriorates the performance of the color barcode system. In this paper, we propose an Expectation Maximization (EM) style algorithm to estimate and cancel this color interference and improve the overall performance of the barcode system. Our method utilizes a physical model for print-capture process where the model parameters vary depending on printer, capture device, and illumination. We estimate the model parameters using an iterative EM-style approach and obtain an estimate of CMY colorant channels from the scanned RGB barcode by using the estimated model parameters. Our experimental results show that the proposed method mitigates the effect of color interference and significantly reduces the bit error rates for the recovered data.