QR Code解碼器的實現

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Thesis > Item 987654321/35732

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35732

Title:	QR Code解碼器的實現
Other Titles:	Implement of QR Code decoder
Authors:	邱柏瑄;Chiu, Po-xuan
Contributors:	淡江大學電機工程學系碩士班簡丞志;Chien, Cheng-chih
Keywords:	錯誤糾正碼;錯誤糾正;ECC;Mask;Error correction capability;RS Code
Date:	2008
Issue Date:	2010-01-11 07:04:50 (UTC+8)
Abstract:	本文中所提及之視能障礙輔助器學習平台，其架構分為八個部分，包含資料建檔、資料編碼、樣本產生、影像擷取、影像處理、錯誤修正、資料解碼、音源連結。我們在本文中會提出具有錯誤修正能力的QR Code，可以解決影像擷取與影像處理時所發生的錯誤，並且敘述QR Code之特性,編碼方式，錯誤修正等級和編碼的驗證。我們把解碼分為兩部份，第一部份為小解碼，包含樣本的大小、儲存的模式、資料的擺放、MASK種類的資料編碼、修正等級…等。第二部份是採用錯誤控制碼中名為Reed-Solomon Code來實現錯誤的修正，我們將這部份歸納為大解碼，負責修正接受到的錯誤資料。本文採用Shortened Reed-Solomon Code演算法與生成多項式結合來達成QR Code樣本的增加，在修正能力的範圍內，可完全修正其錯誤，驗證結果則以Visual C++模擬，未來致力於將平台以DSP實現。 The learning platform for visual disabilities referred to in this paper. Its structure is divided into eight parts, including establishing data base, data encoding, pattern product, image capturing, image processing, error correction, decoding and audio connection. In this paper we will propose QR Code with error-correction capability, which can be solve the errors occurring in image capturing or image processing, and QR code characteristics, encoding modes, ECC levels and encoding verification are introduced in this text. We divide the decoding into two parts. The first part of a small decoding includes the pattern size, storage modes, data placement, encoding MASK types of data, MASK level, etc. The second part takes ECC code named Reed-Solomon Code to achieve the error correction, we summarized this part is responsible for correcting the received error data. This work combine the algorithm of Shortened Reed-Solomon Code with generator polynomial to increase in QR Code patterns. We can correct errors completely within the range of correction capability. Afterward, the results are simulated by Visual C ++. We will achieve that the learning platform can be implemented by DSP hardware in the future.
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Thesis

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