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研究生(外文):Sheng-Chi Tu
論文名稱(外文):Design and Implementation of Real-time License Plate Recognition Systems Based on Embedded Multimedia Development Platform
指導教授(外文):Wen-Hui Chen
口試委員(外文):Ying-Hong LinJun-Zhe Yang
外文關鍵詞:Digital signal processorEmbedded SystemImage processingLicense plate recognition
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近年來國人擁有自用小客車的人數日益漸增,衍生出違規停車、失竊、事故、停車場管理等社會問題,自動車牌辨識可以用來輔助處理這些問題。數位訊號處理器具有執行速度快、高效率、體積小以及適合獨立運作等優點,因此本研究採用德州儀器DM6437 EVM為開發平台,並搭配攝影機建構一套即時車牌辨識系統。實作車牌辨識系統之流程主要有三個階段:(1)車牌定位;(2)車牌字元分割;(3)車牌字元辨識。首先在影像前處理方面利用直方等化、二值化、邊緣檢測、形態學、連通物件等方法,解決所擷取的影像過亮和過暗的問題,並去除非車牌區域之背景及雜訊,再透過投影法從大小不同的車牌上,將字元分割出來,最後以簡單快速的模板匹配法找出與模板相似度最高之字元作為辨識結果。為驗證本文所提方法之可行性,我們以停車場為例進行實測,實驗結果顯示,平均辨識速度為180 毫秒,車牌定位成功率為90.5%,字元辨識率為96.5%,整體車牌辨識準確度達81.25%。

In recent years, the number of car owners has increased, leading to a rise in social issues such as parking violations, thefts, accidents, and parking management. However, automatic license plate recognition can be employed to address these issues. Digital signal processors offer the advantages of high processing speeds, high efficiency, a compact size, and independent operation. Therefore, for this study, we selected Texas Instrument DM6437 EVM as the development platform, which we combined with a video camera to develop a real-time license plate recognition system. Implementation of the license plate recognition system comprises the following three stages: (1) license plate detection; (2) license plate character segmentation; and (3) license plate character recognition. First, image processing methods, such as histogram equalization, binarization, edge detection, mathematical morphology, and connected component labeling, were used to ensure that the captured images were neither excessively bright nor excessively dark and to remove the background and noise signals in the license plate area. Then, the projection method was used to segment the characters on license plates of varying size. Finally, template matching, which is simple and rapid, was employed to select the characters that were the most similar to the template as the recognition result. A parking lot was selected to test the feasibility of this study. The results show that the average recognition speed was 180 milliseconds, the license plate detection success rate was 90.5%, the character recognition rate was 96.5%, and the overall accuracy of the license plate recognition reached 81.25%.

中文摘要 i
英文摘要 ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 文獻回顧 2
1.4 論文貢獻 5
1.5 論文架構 6
第二章 車牌辨識系統 7
2.1 色彩空間 7
2.2 影像前處理 7
2.2.1 直方圖等化 8
2.2.2 二值化 9
2.3 邊緣檢測 11
2.4 形態學 12
2.4.1 膨脹 12
2.4.2 侵蝕 13
2.4.3 閉合 14
2.5 中值濾波器 15
2.6 連通物件標籤 16
2.7 濾除非最大的區域 17
2.8 投影法 17
2.9 字元分割 19
2.10字元辨識 20
第三章 嵌入式系統架構 21
3.1 DaVinci介紹 21
3.2 TMS320DM6437評估版 23
3.3 TMS320DM6437系統核心 24
3.3.1 硬體概述 24
3.3.2 增強式直接記憶體存取控制器 26
3.3.3 視訊處理子系統 27
3.4 Code Composer Studio整合開發環境 30
3.5 基本輸入輸出系統 35
第四章 實驗結果與討論 37
4.1 系統架構 37
4.2 實驗結果與討論 40
4.2.1 實驗設計與結果 40
4.2.2 車牌定位結果 43
4.2.3 字元辨識結果 48
4.2.4 系統執行效能測試 50
第五章 結論與未來工作展望 52
5.1 結論 52
5.2 未來工作與展望 52
參考文獻 54

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