「微字藝術QR碼」是一種將QR碼嵌入微字藝術的新藝術媒介，跟一般微字藝術不同，是一個機械也能辨識內容的微字藝術，能給予觀賞者更多的驚喜。但由於微字藝術擁有獨特的設計感與渲染方式，直接以影像或以半色調的方法與QR碼結合都是不可行的。因此，本論文提出一套產生微字藝術QR碼的演算法，利用微字藝術文字富高頻變化的特性，針對文字結構和字體粗細，設計將QR碼嵌入微字藝術的變形方法。然而，本方法成功最重要的貢獻在於我們能預測QR碼正確解讀的機率。關於這一點，本研究QR碼品質檢測使用大眾化解讀器實驗大量模你的QR碼，以便訓練QR碼解讀成功的機率模型，接著將這個QR碼品質檢測用在整個微字藝術QR碼產生的過程，以確保最後的QR碼可以解讀。最終，本研究以實驗和使用者測驗證實能夠處理極多樣輸入，且多方評估演算法中每一步驟的成效，以便於維持QR碼的可讀性。

This paper presents an algorithm for creating {\em micrography QR codes}, a novel machine-readable micrography generated by embedding a QR code in a micrography image. The unique structure of micrography renders existing methods designed for combining a QR code with a natural or halftone images infeasible. We exploit the high frequency nature of micrography to design a novel combination method that skillfully deforms the individual letters and adjusts their font weights to embed a QR code into a micrography. A critical component to the success of our method is a {\em QR code quality measure} that predicts the chance of correctly decoding a deformed QR code. This quality measure is learned from decoding experiments on synthetic QR codes with popular decoders, and monitors the whole process to guarantee the final result QR code can be decoded. Experiments and user studies demonstrate the strength of our method on a wide variety of inputs, and extensively evaluate each component in our method.

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