基于神經(jīng)網(wǎng)絡(luò)的車牌識別技術(shù)研究
發(fā)布時間：2019-06-11 00:57
【摘要】： 車牌自動識別系統(tǒng)是以汽車牌照為特定目標的專用計算機視覺系統(tǒng)。它的研究主要涉及到了模式識別和人工智能、計算機視覺、數(shù)字圖像處理、人工神經(jīng)網(wǎng)絡(luò)等眾多的學科領(lǐng)域。本文通過對車牌識別系統(tǒng)中車牌定位、圖像預處理、傾斜矯正、字符分割、字符識別五個關(guān)鍵環(huán)節(jié)的分析研究,設(shè)計了一個完整的車牌識別系統(tǒng),并在MATLAB環(huán)境下進行了仿真模擬。 在車牌的定位部分,本文采用的是基于顏色特征和紋理特征的車牌定位方法。首先將彩色圖片從RGB空間轉(zhuǎn)換到HIS空間,利用藍底白字車牌中藍色的色度和飽和度S值較大的特點,實現(xiàn)了車牌的粗定位。然后再對粗定位后的圖像利用Canny算子進行邊緣檢測,根據(jù)車牌部分圖像黑白跳變頻率較高的特征,最終實現(xiàn)了車牌的精確定位。 在圖像的預處理部分,本文將得到的車牌定位圖像進行了灰度化處理,利用Otsu法將灰度圖像轉(zhuǎn)換為二值圖像,并給出了一種灰度圖像增強算法,對采集到的車牌圖像進行增強處理;由于在實際中車牌的邊框和上下鉚釘會對車牌的識別工作形成干擾,因此在該部分中對車牌的邊框和鉚釘進行了去除。 在獲取車輛圖像的過程中,由于攝像機和車牌之間角度的變化,經(jīng)常使所拍攝的車輛圖像發(fā)生傾斜,導致車牌扭曲和字符變形,給字符分割和字符識別帶來極大影響。為此,文章研究了一種基于空間扭曲校正和Hough變換的車牌圖像校正方法。 在字符的分割部分,本文依據(jù)現(xiàn)行的車牌設(shè)計原則,利用改進后的水平投影法,將車牌圖像分割7個待識別字符,并對分割后的字符進行了歸一化處理。實踐證明該方法對解決漢字的不連通問題、字符的粘連問題、噪聲的干擾問題以及車牌的前2個字符和后面5個字符之間存在的小圓點問題是行之有效的。 在字符的識別部分,采用改進后的BP神經(jīng)網(wǎng)絡(luò),針對漢字、字母、字母或數(shù)字、數(shù)字四種不同的識別問題,設(shè)計了四種不同的分類器。利用13特征提取法進行特征提取,將其結(jié)果作為網(wǎng)絡(luò)的輸入,最后將不同的識別結(jié)果組合得到車牌號碼。
[Abstract]:Automatic license plate recognition system is a special computer vision system with automobile license plate as a specific target. Its research mainly involves pattern recognition, artificial intelligence, computer vision, digital image processing, artificial neural network and many other disciplines. Based on the analysis and research of license plate location, image preprocessing, tilt correction, character segmentation and character recognition in license plate recognition system, a complete license plate recognition system is designed in this paper. The simulation is carried out in MATLAB environment. In the part of license plate location, this paper adopts the license plate location method based on color features and texture features. Firstly, the color picture is converted from RGB space to HIS space, and the rough location of license plate is realized by using the characteristics of blue chromaticity and saturation S in the license plate with blue background and white character. Then the edge detection of the rough positioning image is carried out by Canny operator. According to the high black and white jump frequency of some images of the license plate, the accurate location of the license plate is finally realized. In the part of image preprocessing, the license plate location image is grayed out in this paper, and the gray image is converted into binary image by Otsu method, and a gray image enhancement algorithm is proposed. The collected license plate image is enhanced. In practice, the border and rivets of license plate will interfere with the recognition of license plate, so the border and rivet of license plate are removed in this part. In the process of obtaining vehicle images, due to the change of the angle between the camera and the license plate, the vehicle image is often tilted, which leads to the distortion of the license plate and the deformation of the characters, which has a great impact on character segmentation and character recognition. In this paper, a license plate image correction method based on spatial distortion correction and Hough transform is studied. In the part of character segmentation, according to the current license plate design principles, this paper uses the improved horizontal projection method to segment seven characters to be recognized, and normalizes the segmented characters. It is proved by practice that this method is effective to solve the problem of disconnectedness of Chinese characters, adhesion of characters, interference of noise and the problem of small dots between the first two characters and the last five characters of license plate. In the recognition part of characters, four different classifiers are designed for four different recognition problems of Chinese characters, letters or numbers and numbers by using the improved BP neural network. The 13 feature extraction method is used for feature extraction, and the results are used as the input of the network. Finally, different recognition results are combined to get the license plate number.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2009
【分類號】：TP391.41
本文編號：2496872
[Abstract]:Automatic license plate recognition system is a special computer vision system with automobile license plate as a specific target. Its research mainly involves pattern recognition, artificial intelligence, computer vision, digital image processing, artificial neural network and many other disciplines. Based on the analysis and research of license plate location, image preprocessing, tilt correction, character segmentation and character recognition in license plate recognition system, a complete license plate recognition system is designed in this paper. The simulation is carried out in MATLAB environment. In the part of license plate location, this paper adopts the license plate location method based on color features and texture features. Firstly, the color picture is converted from RGB space to HIS space, and the rough location of license plate is realized by using the characteristics of blue chromaticity and saturation S in the license plate with blue background and white character. Then the edge detection of the rough positioning image is carried out by Canny operator. According to the high black and white jump frequency of some images of the license plate, the accurate location of the license plate is finally realized. In the part of image preprocessing, the license plate location image is grayed out in this paper, and the gray image is converted into binary image by Otsu method, and a gray image enhancement algorithm is proposed. The collected license plate image is enhanced. In practice, the border and rivets of license plate will interfere with the recognition of license plate, so the border and rivet of license plate are removed in this part. In the process of obtaining vehicle images, due to the change of the angle between the camera and the license plate, the vehicle image is often tilted, which leads to the distortion of the license plate and the deformation of the characters, which has a great impact on character segmentation and character recognition. In this paper, a license plate image correction method based on spatial distortion correction and Hough transform is studied. In the part of character segmentation, according to the current license plate design principles, this paper uses the improved horizontal projection method to segment seven characters to be recognized, and normalizes the segmented characters. It is proved by practice that this method is effective to solve the problem of disconnectedness of Chinese characters, adhesion of characters, interference of noise and the problem of small dots between the first two characters and the last five characters of license plate. In the recognition part of characters, four different classifiers are designed for four different recognition problems of Chinese characters, letters or numbers and numbers by using the improved BP neural network. The 13 feature extraction method is used for feature extraction, and the results are used as the input of the network. Finally, different recognition results are combined to get the license plate number.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2009
【分類號】：TP391.41
【引證文獻】
相關(guān)碩士學位論文 前10條
1 鹿琛;基于神經(jīng)網(wǎng)絡(luò)的車牌識別技術(shù)研究[D];山西大學;2017年
2 尹川;基于Android系統(tǒng)的車牌識別系統(tǒng)的設(shè)計與實現(xiàn)[D];哈爾濱工程大學;2017年
3 隋君;基于數(shù)字圖像處理技術(shù)的車牌識別系統(tǒng)研究[D];吉林大學;2016年
4 張冠華;一種基于神經(jīng)網(wǎng)絡(luò)的車牌識別方法的實現(xiàn)[D];吉林大學;2016年
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8 柯昊宇;電子警察在城市道路交通監(jiān)控系統(tǒng)中的應用研究[D];五邑大學;2012年
9 付燃;車牌識別系統(tǒng)中牌照定位和預處理技術(shù)的研究[D];中北大學;2012年
10 丁姍;基于神經(jīng)網(wǎng)絡(luò)集成的車牌字符識別研究[D];山東師范大學;2011年
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