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研究生:裴德雄
研究生(外文):De-Xiong Pei
論文名稱:以改良模板匹配方法用於多車牌辨識
論文名稱(外文):Improved Template Matching Methods for Multiple License Plates Recognition
指導教授:郝敏忠
指導教授(外文):Miin-Jong Hao
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:電腦與通訊工程研究所
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:2014
畢業學年度:102
語文別:英文
論文頁數:61
中文關鍵詞:車牌識別投影法數學形態學中值濾波連通區域法邊緣檢測模板匹配
外文關鍵詞:License plate recognitionMedian filtersEdge
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  • 被引用被引用:2
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自動車牌識別在自動化和智能交通系統管理上扮演非常重要的作用。目前的車牌識別系統只能識別單目標,無法進行多目標識別。在實際應用面,相機拍攝的圖像可能具有多個目標,單目標識別會放棄很多信息降低效率。為了改善這種車牌識別系統,本論文提出一種新的模板匹配方法以及改進一些影像處理技術供車牌識別,然後整合起來既有建立一個高精度多個車牌識別系統。
本論文所提出之高精度多個車牌識別系統分為預先處理,車牌區域分離,字元分割,以及字元識別等四部分。首先,預處理部分使用中值濾波器,邊緣檢測,數學形態學和連通域分析法找出可能的車牌區域。然後,在可能區域內我們使用基於字元特徵垂直投影法來確認車牌區域。在字元分割部分,本文採用之方法是以投影法為基礎,最後,字元識別是採用本文所提出的新模板匹配方法。
實驗結果顯示,我們所提出的系統可以在一張有複雜的背景影像中有效地定位以及識別多個車牌。整體實驗結果顯示,所提出的系統對於單目標辨識準確率達91.5%,以及對於多目標的辨識準確率為90.9%。
Automatic license plate recognition plays a very important role in the management of automation and intelligent transportation systems. However, the license plate recognition systems at the present day can only recognize a single target. In practice applications, an image captured from the camera may contain multiple targets. Many pieces of information will be left behind if the single-target license plate recognition system is applied to such a picture. To reform the license plate recognition system, a new template matching method is proposed and several image processing schemes for character recognition are modified. As a consequence of integrating the proposed and reforming schemes, a multiple-target license plate recognition system of high precision is developed and established.
The multiple-target license plate recognition system is comprised of preprocessing, plate-region detection, character segmentation, and character recognition. First in the preprocessing part, the median filter is used. The edge detection, mathematical morphology, and connected component labeling methods are used in sequence to find out possible regions of license plates. Then the vertical projection method based on characters’ features is applied in the ranges of possible regions for ensure the regions of license plates. The projection method is used for character segmentation then, and the proposed template matching scheme is used for character recognition
Experimental results show that the proposed template matching method is robust in extracting and recognizing multiple license plates from the image with a complex background. Our experiments also show that the proposed license plate recognition system has 91.5% of the accurate rate for a single target recognition and 90.9% of the accurate rate for multi-target recognition.
Abstract in Chinese..........................................................................................I
Abstract in English..........................................................................................II
致謝..................................................................................................................IV
Contents............................................................................................................V
List of Figures ……..........................................................................................VIII
List of Tables…….............................................................................................XI
Chapter 1 Introduction .................................................................................... 1
Chapter 2 Literature Review and Related Technology……………..........…3
2.1 Literature Review …………….............................................................. 3
2.1.1 License Plate Localization…………………………………..…...3
2.1.2 Character Segmentation…………………………………….……4
2.1.3 Character Recognition……………………………………...…....5
2.2 Vehicle License Specifications in Taiwan..............................................6
2.3 Related Technology................................................................................7
2.3.1 Median Filter……………………………………………………..7
2.3.2 Edge Detection..............................................................................8
2.3.3 Binarization...................................................................................9
2.3.4 Morphological Processing............................................................12
2.3.5 Connectivity…………………….................................................13
2.3.6 Normalization..............................................................................16
2.3.7 Projection Method………………………………………….…..17
Chapter 3 Framework of License Plate Recognition System………….…..19
3.1 The Pre-processing Procedure..............................................................20
3.1.1 Color To Gray Images................................................................ 21
3.1.2 Median Filter………………………………………………...….21
3.1.3 Sobel Edge Detection……………………………………….…..23
3.1.4 Image Binarization………………………………………….…..24
3.1.5 Morphological Processing……………………………….….….25
3.2 Detection Procedure of License Plate…………………………………28
3.3 Character Segmentation Procedure…………………………………...36
3.3.1 Binarization Invers……………………………………..….……38
3.3.2 Projection Method……………………………………………...39
3.3.3 Connected Component…………………………………..……..41
3.3.4 Angle Calibration……………………………………………….42
3.3.5 Character Segmentation…………………………………………44
3.4 Character Recognition Procedure..........................................................45
3.4.1 Character Normalization.............................................................46
3.4.2 Character Database.....................................................................46
3.4.3 Character Recognition.................................................................48
Chapter 4 Experiment Results and Discussion............................................50
4.1 Experiments..........................................................................................50
4.2 Results..................................................................................................51
4.2.1 License Plate Detection…………………………………….……52
(1) Single Target..........................................................................52
(2) Multi-Target...........................................................................53
4.2.2 Character Segmentation……………………………….…………53
(1) Single Target...........................................................................53
(2) Multi-Target............................................................................53
4.2.3 Character Recognition…………………………………………...54
(1) Single Target...........................................................................54
(2) Multi-Target............................................................................54
4.3 Causes of Incorrect Detection for License Plates………………………54
4.4 Discussion...............................................................................................56
Chapter 5 Conclusions……………………………………………..……..……57
References...........................................................................................................59
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