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研究生:黃啟銘
研究生(外文):Chi-Ming Huang
論文名稱:移動中車輛之車牌自動辨識之研究
論文名稱(外文):The Study on License-Plate Recognition for Moving Vehicles
指導教授:陳昭和
指導教授(外文):Chao-Ho Chen
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電子工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:84
中文關鍵詞:車牌辨識車牌定位影像處理邊緣偵測
外文關鍵詞:License Plate RecognitionVehicle Plate LocatingImage ProcessingEdge Detection
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車牌辨識(License Plate Recognition,LPR)的應用十分廣泛,但過去的研究大多是著重在靜態系統之研究,以感應觸發的方式擷取車輛之影像。在本論文中,是以一固定架設的攝影機連續拍攝車道出入口(閘道),運用電腦視覺與影像視訊處理之方式,先將視訊中移動的車牌定位出來再加以辨識。由於本研究之攝影機是架設於室外,而室外環境很容易受到天氣的影響(例如,下雨),因此本論文將提出能被使用於一般及雨天環境下之移動中車輛之車牌辨識方法。
本方法之主要原理是先利用梯度分析找出影像中之邊緣部份,而習知二值化方法在雨天環境下並不能降低影像之複雜度,故在此部分本文提出梯度分析二值化法,來執行此階段之二值化處理,接著,再利用本文所提出的車牌定位方法尋找車牌所在位置,然後利用水平投影分析法加以判斷目前所定位到的區域是否為車牌,接著,將定位出來的車牌影像擷取出來,以便後續執行字元辨識處理。而擷取出來之車牌影像必須重新調整邊界,使得車牌影像僅剩字元部份,接下來再執行字元切割處理,最後,使用樣板比對(Template Matching)之方式來完成字元辨識處理。
實驗結果顯示本文所提出之方法可即時有效地辨識緩慢行駛移動中的車輛之車牌,在晴天環境下,車牌定位的成功率可達91.51%,車牌辨識的成功率可達84.54%;在雨天環境下,車牌定位的成功率可達90.59%,車牌辨識的成功率81.81%。
License plate recognition system is widely used in the present time, but most of the previous researches emphasized on static system. In this thesis, a license plate location and recognition method is proposed to shoot the motion-based vehicle by the video camera set up in KUAS’s entrances and exits. As a result of the video camera was set up in outdoor environment, therefore rainy environment will impact on the system. Hence this thesis will propose a license plate recognition method for moving vehicles applied in both environments.
The principle of license plate recognition is utilizing gradient analysis and the license plate location method of this thesis proposed to find out the precise position of the license plate. Then, the located license plate must pass through boundary re-adjusting、character segmentation and character recognition with template matching to finish the license plate recognition system.
In general environment, the result shows the accuracy of license plate location is 91.51%, and the accuracy of license plate recognition is 84.54%. In rainy environment, the accuracy of license plate location is 90.59%, the accuracy of license plate recognition is 81.81%. The processing time of this system needs only 40~60mS, and conforms to the requirement of real-time system.
摘 要..........I
ABSTRACT..........III
誌 謝..........V
目錄..........VI
圖目錄..........VIII
表目錄..........X
第一章、緒論..........1
1.1 研究背景..........1
1.2 文獻探討..........2
1.2.1 車牌定位文獻探討..........2
1.2.2 字元切割與字元辨識文獻探討..........3
1.3 系統架構與流程..........5
1.4 論文架構..........8
第二章、習知研究方法..........9
2.1 邊緣偵測之方式..........9
2.1.1 Robert邊緣偵測運算..........11
2.1.2 Sobel邊緣偵測運算..........12
2.1.3 Kirsch邊緣偵測運算..........13
2.1.4 Canny邊緣偵測運算..........14
2.2 車牌定位方法..........18
2.2.1 邊緣及高對比度特性..........18
2.2.2 顏色特性..........19
2.3.1 樣版比對(Template Matching)..........21
2.3.2 直方圖比對(Histogram Matching)..........21
2.3.3 支撐向量機SVMs..........22
2.4 影像二值化..........29
2.4.1 固定門檻二值化法..........29
2.4.2平均值二值化法..........30
2.4.2 Otsu二值化法..........30
2.5 形態學運算..........32
2.6 投影法..........35
第三章、車牌定位..........37
3.1 影像前處理..........38
3.2 邊緣偵測..........38
3.3 二值化處理..........40
3.4 形態學處理..........49
3.5 車牌定位方法..........50
第四章、字元辨識..........56
4.1 邊界調整..........57
4.2 字元切割..........58
4.3 字元辨識..........63
第五章、實驗結果..........66
第六章、結論與未來方向..........74
6.1 車牌定位錯誤討論..........74
6.2 字元辨識錯誤討論..........76
6.3 結論..........77
參考文獻..........79
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