臺灣博碩士論文加值系統

在先進的照相手機中，有一個新的應用，你可以使用相機手機對著二維條碼拍照，並且解碼出二維條碼的內含資訊。但是在先前的演算法並沒有考慮QR code在不均勻光線和複雜背景情形下。在這篇論文中，我們提出了一個有效的演算法從不均勻和複雜背景的圖像中擷取出QR code，並且實作在嵌入式系統中。我們的演算法可以準確的擷取出光線不足和形狀歪斜的QR code。實驗結果可以顯示出我們的演算法不僅效率高，而且可以實作在內置相機的嵌入式系統上。

In the advanced applications on camera phones, you can take a picture containing a QR code using the camera phones to retrieve the content from the decoded QR code. However, for QR-code extraction, previous works do not consider uneven light effects in a non-uniform background image. In this thesis, we propose an efficient approach to extract QR code from the non-uniform background with uneven light effects in embedded mobile phones. Our approach can precisely extract QR code from the images in any bad light conditions and space distortion. The experimental results show that our algorithm is not only efficient but also effective for QR-code extraction in the embedded camera phones.

1 Introduction 1
2 Preliminaries 3
2.1 Barcode Progress......................................3
2.2 Barcode Reader Progress...............................4
2.3 QR code...............................................6
2.4 History...............................................6

2.5 Features..............................................6
2.6 Outlook...............................................7
2.7 Applications..........................................8
2.8 System................................................10
2.8.1 Hardware System.....................................10
2.8.2 Software System.....................................13
2.9 Challenges............................................13
3 EQRE Algorithm 16
3.1 Changing Color Space..................................16
3.2 Binary Process........................................16
3.3 QR-code Detection.....................................19
3.3.1 Finding Three Finder Patterns.......................19
3.3.2 Finding Three Corners...............................21
3.3.3 Finding Fourth Corner...............................22
3.3.4 Inverse Perspective Transformation..................22
3.4 Re-sampling Transformation............................25
4 Experimental Results 27
4.1 Light Condition Analysis..............................28
4.2 Perspective Angle Analysis............................31
4.3 Efficiency Analysis...................................32
4.4 Limitation............................................33
5 Conclusions and FutureWorks 35

[1] ARM, http://www.arm.com/.
[2] CBC Corporated, http://www.cbc-mirunet.com/.
[3] CHUBUelectric power, http://www.chuden.co.jp/english/corporate/press2005/0209_1.html.
[4] Cmode service, http://www.cmode.jp/.
[5] Denso Wave Incorporated, http://www.denso-wave.com/en/index.html.
[6] Denso Wave Incorporated, http://www.qrcode.com/.
[7] ITmedia Incorporated, http://www.itmedia.co.jp/bizid/articles/0606/22/news059.html.
[8] SUNWISH, http://www.qrclip.net/.
[9] Taiwan Agriculture and Food Traceability System, http://taft.coa.gov.tw/welcome.swf.
[10]Yahoo JAPAN, http://sp.mobile.yahoo.co.jp/mobile/.
[11]J. X. 0510. Two dimensional symbol – QR Code – Basic specification. 1999.
[12]I. 18004:2000. Information technology - Automatic identification and data capture techniques - Bar code symbology - QR Code. 2000.
[13]AIM. ISS QR Code. 1997.
[14]Y.-H. Chang, C.-H. Chu, and M.-S. Chen. A general scheme for extracting qr code from a non-uniform background in camera phones and appilcations. Master Thesis in National Taiwan University, January 2007.
[15]Y. Ebrahim, W. Abdelsalam, M. Ahmed, and S.-C. Chau. Proposing a Hybrid Tag-Camera-Based Identification and Navigation Aid for the Visually Impaired. IEEE International Conference on Consumer Communications and Networking Conference, 2004.
[16]H. Kato and K. T. Tan. 2D Barcodes for Mobile Phones. IEEE 2nd International Conference on Mobile Technology, Applications and Systems, 2005.
[17]L. Naimark and E. Foxlin. Circular Data Matrix Fiducial System and Robust Image Processing for aWearable Vision-Inertial Self-Tracker. IEEE International Symposium on Mixed and Augmented Reality, ISMAR, Proceedings, 2002.
[18]E. Ohbuchi, H. Hanaizumi, and L. A. Hock. Barcode Readers using the Camera Device in Mobile Phones. In Proc. of IEEE International Conference on Cyberworlds, 2004.
[19]T. S. Parikh and E. D. Lazowska. Designing an Architecture for Delivering Mobile Information Services to the Rural Developing World. IEEE Workshop on Mobile Computing Systems and Applications, 2006.
[20]W. K. Pratt. Digital Image Processing. JohnWiley and Sons, 2001 (third edition).