(1東南大學生物科學與醫學工程學院，江蘇省 南京 10096；2.東南大學計算機科學與技術學院，江蘇省南京 210096）
摘 要：車牌識別技術在現代智能交通系統中有越來越重要的應用（如收費站、停車場的車輛檢測系統）。為了有效的檢測一個車牌，尋找車牌的位置是最關鍵的一步。本文提出了一種基于邊緣的復雜背景下車牌的檢測算法。該方法綜合利用圖像對比度增強、邊緣檢測、形態學處理、連通域分析、矩形性質分析等多種方法,解決了復雜背景中車牌定位難的問題,能夠準確定位雜亂背景中的車牌,對天氣、光照變化、車牌在圖像中的移動和旋轉等具有良好的適應能力，該方法為后續的字符分割和字符區域定位信息、車牌的超分辨率重建帶來了方便。
關鍵詞：邊緣檢測;連通域分析;形態學處理；矩形性質分析；
中圖分類號：TP 文獻標識碼：A 文章編號：
A Adaptive License Plate Detection Algorithm For Complex Background
WANGHeng, LUOLimin
(1. School of Biomedical Engineering, Southeast University, Nanjing, 210096，China. WANGHeng ,wanghengq1h2@126.com
2. School of Computer Science and Technology, Southeast University, Nanjing, 210096,China.LUOLimin,luo.list@seu.edu.cn)
Abstract：License plate detection plays a more and more important role in modern intelligent transportation systems .In order to identify a license plate effectively, accurate license plate localization is the key step before the final recognition.This paper presents a adaptive license plate detection algorithm for complex background.The approach includes contrast enhancement, edge detection, morphological deal, connected component analysis, rectangularity analysis. The results demonstrate the effectiveness and robustness of the proposed method. Our results can be used in character segment and Super-Resolution Image Reconstruction .
Key words：Edge detection; Connected component analysis; Morphological deal; Rectangularity analysis
參考文獻 (References)
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作者簡介：
王衡（1987－），男，山東淄博人，碩士研究生，2010年于東南大學獲得學士學位，主要從事圖象處理方面的研究。
