臺灣博碩士論文加值系統

本論文提出一套具有電腦視覺功能的自主式車牌偵測與辨識系統。本系統可分為四個子系統：車輛偵測子系統、車牌擷取子系統、字元切割子系統與字元辨識子系統，其中車輛偵測子系統利用動態影像之移動總量與移動位置特性去定位出車輛位於畫面上的確切位置，而車牌擷取子系統利用車牌特性與車牌搜尋演算法去擷取車牌，字元切割子系統則結合Tophat、Labeling與一次線性迴歸進行自動切割功能；至於字元辨識子系統，我們比較了支援向量機與倒傳遞類神經網路的辨識效果，最後則選擇倒傳遞類神經網路來當最後字元的辨識器。實驗結果證實本系統能有效的偵測車輛與辨識不同光線情形下的車牌。

The paper proposed an autonomous license plate detection and recognition system with computer vision. The system consists of four subsystems: car detection subsystem, plate extraction subsystem, character division subsystem and character recognition subsystem. Car detection subsystem uses MMADR and NDDR of dynamic image to find the location of the cars on the screen. Plate extraction subsystem uses the characteristics of the plates and algorithm used to search plates to extract plate; character division subsystem combines Tophat, Labeling and LRE to automatically divide. As to character recognition subsystem, after comparing identification effects of SVM and BPNN, we choose BPNN as the recognizer. Experiment outcome proves that our system can effectively detect cars and recognize the plates under different lights.

中文摘要 i
英文摘要 ii
致謝 iii
目錄 iv
表目錄 v
圖目錄 vi
第一章 序論 1
1-1 動機與目的 1
1-2 相關研究 3
1-3 系統架構 4
1-4 章節簡介 6
第二章 車輛偵測 7
2-1 最低移動總量判斷法則 12
2-2 最近距離判斷法則 15
第三章 車牌擷取 19
第四章 字元切割 23
4-1 影像強化 24
4-2 去除雜訊 25
第五章 字元辨識 29
第六章 實驗結果 30
6-1 實驗平臺 30
6-2 實驗一 32
6-3 實驗二 32
6-4 實驗三 33
6-5 實驗四 38
第七章 結論與未來展望 41
參考文獻 42

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