陳銘憲Chen, Ming-Syan臺灣大學:電信工程學研究所林陳鍵Lin, Chen-ChienChen-ChienLin2010-07-012018-07-052010-07-012018-07-052009U0001-0302200909101400http://ntur.lib.ntu.edu.tw//handle/246246/188261近幾年來,隨著行動通訊裝置的快速發展與功能不斷的推陳出新,我們可以在任何時間,地點使用任何方法取得我們所需要的資訊,在眾多的方法中,又以QR code的應用是最受消費者所歡迎的,其中現在新的應用則是使用照相手機對著顯示器上所顯示的QR code 做拍照來獲得相關訊息。但是,隨著照像手機的照相解析度越來越高,當我們使用此高解析度的照相手機擷取顯示器的 QR code 時,常常會被顯示器上單位畫素所產生的干擾所影響,而造成無法解碼判讀的情況發生。此,我們提出一個有效的QR code雜訊濾除方法,使用此濾除方法可以有效地濾除上述所提的畫素干擾雜訊,又較不會影響圖像的清晰度,因此,可以提高 QR code的解碼判讀率,另外,我們也會將此濾除方式應用在嵌入式系統中,並與其他常見的影像濾波處理作比較。由實驗結果可知道,在經過我們的方法濾波處理後,被雜訊所干擾的圖像在解碼辨識失敗率上都有很明顯地改善許多。In the recent years, with the rapid advances in the wireless mobile communication technologies and applications, mobile users can obtain information of their requirement from anytime, anywhere, via wireless mobile devices. In these mobile phone applications, the QR-code applications are popular function. In recent applications, users can take a QR-code pattern from the displayer for obtaining their required information. However, if users use high-resolution camera modules in the mobile phone to take QR-code patterns from displayer, the taken image suffers from interference at the pixels from the displayer. Such interference affects QR-code recognition.n this thesis, we propose QR-code denoisy filter to efficiently and effectively filter out these noises and also to preserve the edges of the image on the noisy QR-code patterns. This QR-code denoisy filter processing also can be applied to embedded mobile phones. We also conduct several experiments to evaluate the quality and the performance of our QR-code denoisy filter.s compared to other filters, the experimental results show that our approach can achieve the higher QR-code recognition and a comparable running speed.Contents Introduction...........................................1 Preliminaries..........................................32.1 Barcode Introduction................................32.2 AboutQRCode.........................................42.3 QR Code Introduction................................5 2.3.1 Overview.........................................5 2.3.2 SymbolVersion....................................6 2.3.3 ModuleSize.......................................7 2.3.4 About Securing Margin............................72.4 QR Code Currently Application.......................72.5 Frequency-scanning Noise Distortion on Display......82.6 ProblemFormulation.................................102.7 System.............................................10 2.7.1 Hardware Development System.....................10 2.7.2 Software Development System.....................112.8 Challenges.........................................13 Digital Image Processing..............................143.1 MeanFiltering......................................143.2 GaussianFiltering..................................153.3 QR-code Denoisy Filtering..........................17 3.3.1 RGBToGray.......................................18 3.3.2 Mean filtering processing.......................18 3.3.3 Intensity Domain Gaussian filtering processing..193.4 BilateralFiltering.................................20 Experimental Results..................................234.1 Camera Resolution Analysis.........................254.2 Digital Image Filter Processing Analysis...........274.3 QR-code Denoisy Filter Processing Analysis.........304.4 Running Time of Denoisy Filter Processing Analysis.32 Conclusions and FutureWorks...........................332240349 bytesapplication/pdfen-US影像處理影像濾波QR code行動電話嵌入式系統照相機模組image processingimage filteringmobile phoneembedded systemcamera modulethesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/188261/1/ntu-98-P95942006-1.pdf