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  本文關(guān)鍵詞：基于視頻圖像的車輛檢測和車牌識別　出處：《寧夏大學》2017年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 車輛檢測 車牌定位 傾斜校正 字符分割 字符識別

【摘要】：車牌識別系統(tǒng)是智能交通系統(tǒng)(Intelligent Transport System,簡稱ITS)的一個重要組成部分,車牌識別在城市交通管理、停車場管理、小區(qū)車輛出入、高速公路收費等方面有著廣泛的應用,對于城市道路交通卡口系統(tǒng)而言,高效的對車輛進行檢測、對車牌進行識別是協(xié)助破獲肇事逃逸、車輛違章和車輛丟失等事件的有效手段。在車牌識別系統(tǒng)中,能否檢測到運行車輛并對運行車輛進行準確的車牌定位對車牌字符的識別有著極其重要的影響,不能準確的定位到車牌就不能進行字符識別,因此本文會重點對車輛檢測和車牌定位進行深入研究,并提出一種新的車輛檢測和車牌定位方法,并在Matlab平臺上編程實現(xiàn),實驗結(jié)果表明了該方法的有效性。本文的主要研究內(nèi)容包括以下幾個方面:運動車輛的檢測。分析了目前常用的一些前景提取方法的優(yōu)缺點,在Matlab上分別編程實現(xiàn)其中三種提取車輛的方法,對比實驗結(jié)果并分析。根據(jù)實際需要選擇背景差分法的平均值背景模型并結(jié)合車輛的梯度圖像檢測目標車輛,最后使用形態(tài)學方法和二值化方法提取完整的目標車輛。車牌定位。簡要介紹目前針對車牌定位常用的一些方法,分析它們的優(yōu)缺點,通過實驗驗證一些車牌定位方法存在的缺點,例如,邊緣檢測方法對于圖像質(zhì)量較差的車輛圖片的車牌定位存在很大的誤差。根據(jù)這些缺點提出一種結(jié)合邊緣檢測和顏色特征的車牌定位方法,并進行實驗驗證該方法的可靠性。車牌傾斜校正與字符分割。成功定位到車牌后需要為車牌識別做準備工作,定位到的車牌往往存在傾斜和定位的精確度不夠的問題,根據(jù)這些問題選擇一些算法校正傾斜車牌,校正后的車牌根據(jù)垂直投影法進行精確定位并分割車牌字符。字符識別。分析目前現(xiàn)有的車牌字符識別算法,結(jié)合實際情況選擇合適的算法識別車牌字符。
[Abstract]:License plate recognition system is the intelligent transportation system (Intelligent Transport System, referred to as ITS) is an important part of license plate recognition in city traffic management, parking lot management, vehicle access, is widely used for highway tolls, city road traffic monitoring system, efficient detection of the vehicle, the license plate recognition is to assist cracked escapes, effective means of vehicle peccancy and vehicle loss events. In the license plate recognition system can detect vehicle operation and the operation of the vehicle license plate accurately is very important for the license plate character recognition, can not accurately to locate the license plate character recognition is not so. This paper will focus on in-depth study of vehicle detection and license plate location, and proposed a new vehicle detection and license plate location method, and in Matlab The realization of programming platform, the experimental results show that the method is effective. The main contents of this paper include the following aspects: vehicle detection. Analyzed the advantages and disadvantages of some commonly used foreground extraction method, respectively in Matlab programming method of the three extraction vehicle, and comparative analysis of the experimental results. According to background difference method the average background model based on the detection of target gradient image of the vehicle actual need, the target vehicle finally using morphological method and binarization method for extracting intact. The license plate location. This paper briefly introduces some common methods for locating and analyzing their advantages and disadvantages, through experimental verification of some license plate the positioning methods, for example, the edge detection method for vehicle license plate location picture of poor image quality in the presence of large errors. According to these disadvantages A method combining edge detection and color feature of license plate location method, and experiments are carried out to verify the reliability of the method. The license plate tilt correction and character segmentation. The successful positioning of the license plate to do the preparatory work for license plate recognition, license plate location tend to tilt and positioning accuracy is not enough, some selection algorithm according to the problem vehicle license plate tilt correction, after correction for precise positioning according to the vertical projection and segmentation of license plate characters. Character recognition. Analysis of the existing license plate recognition algorithm, combined with the selected algorithm of license plate character recognition of the actual situation.

【學位授予單位】：寧夏大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U495;TP391.41

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本文編號：1416167