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Micrography QR Codes
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Micrography QR Codes

Shih-Hsuan Hung, Chih-Yuan Yao, Yu-Jen Fang, Ping Tan, Ruen-Rone Lee, Alla ShefferHung-Kuo Chu
IEEE Transactions on Visualization and Computer Graphics, 卷.26(9), 頁碼.2834-2847
09/2020
PMID: 30716038

摘要

image warping Micrography optimization QR code typography Software Signal Processing Computer Vision and Pattern Recognition Computer Graphics and Computer-Aided Design
This paper presents a novel algorithm to generate micrography QR codes, a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective.

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