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  • 學位論文

噴墨印表機多重維度加密與解碼技術的實現

Extrinsic Signature Embedding and Detection for Inkjet-Printed Text Document

指導教授 : 江佩如
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摘要


本文主要研究的目的是藉由噴墨印表機列印的文件來做為追溯的依據,印表機已經是現代社會中不可或缺的印刷工具之一,一般來說,除了特定的印表機,如特殊墨水噴墨頭印表機或者使用特殊列印紙張等方式,否則列印出來的文件經常是可以被仿冒的,因此本研究利用現場可程式化閘陣列(Field-programmable gate array,FPGA)晶片具有平行控制的優點來控制噴墨印表機內光學編碼器的訊號,使列印文件上的文字產生偏移,以達到隱藏訊號的目的,同時為了維持列印品質,隱藏訊號為人眼無法察覺文字上所產生的偏移,之後利用掃描器及影像處理的技術將所隱藏的訊號提取出來,本研究的編碼技術一頁A4文件最多可隱藏56個bits。 本實驗所使用的噴墨印表機為HP-DJ1010,解析度為600 dpi,一頁由亂數選取的英文字母所組成,字體大小設為20pt,間格為單行間距,22列文字所組成的文件,共可隱藏42個bits的編碼,其解碼由於垂直方向的bit錯誤率較高,錯誤率為18.1%,導致解碼時正確率大幅下降,因此本研究同時使用RS錯誤糾正碼來偵測錯誤碼,其結果由30張錯27張經由RS碼偵錯後降低至30張錯11張。

關鍵字

噴墨印表機 影像 文件加密 解碼

並列摘要


Printer identification based on printed documents can provide forensic information to protect copyright and verify authenticity. In this paper, we will demonstrate the feasibility of embedding code sequences in text document by shifting the text line horizontally and vertically through encoder modulation. We have developed corresponding embedding and detection algorithms to embed and extract information. Experimental results indicate that using a 600 dpi inkjet printer, we can encode 21 bits of information in both horizontal and vertical directions, which implies 42 bits in one A4 size of page. The bit errors in horizontal and vertical direction are 7.3% and 18.1%, respectively. Thereby Reed-solomon codes are used to correct the errors. The experimental results show that, through using Reed-solomon codes, the bit errors can be reduced efficiently.

並列關鍵字

inkjet printer image file encryption decoding

參考文獻


[1] Mauro Barni, Christine I. Podilchuk, Franco Bartolini and Edward J. Delp, “Watermark embedding: hiding a signal within a cover Image”, IEEE Communications,pp.39–102 (2001).
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[3] C.-I. Podilchuk , E.-J. Delp, “ Digital watermarking: Algorithms and applications”, IEEE Signal Processing Magazine, pp.18–33 (2001).
[4] Brassil JT; Low S; Maxemchuk NF, “ Copyright protection for the electronic distribution of text documents ”, PROCEEDINGS OF THE IEEE , pp. 1181–1196 (1999).
[8] N. Otsu, “A threshold selection method from gray-level histograms”, IEEE Transactions on Systems, Man, and Cybernetics, pp .62–66(1979).

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