[毕业设计]基于matlab的车牌识别的研究

A1A0A2A3A4A5A6基于MATLAB的车牌识别系统学院电控学院专业交通信息工程及控制姓名学号2010年12月A7A8A9A10A11A12A13目录4A14A15A16A17A18A19A20A21A22A23A24A25A26A27A28A29A30A31A30A31A30A31A32A32A33A34A35A36A37A35A36A38A39A40A41A42A43A44A294A45A40A41A42A46A475A48A49A50A40A51A52A44A53A54A55A56A575A48A39A50A40A58A59A60A61A62A63A64A658A48A45A50A40A66A67A60A64A65A68A69A49A7010A48A71A50A40A66A67A60A72A7311A45A40A41A42A74A75A53A64A7613A71A40A77A7414A78A40A79A80A81A8214A83A84A85A86A87A88A89A90A91A92A93A94A95A96基于MATLAB的车牌识别的研究A97A98A99A100A101A102A103A104A105A106A107A108A109A110A111A107A112A113A114A115A107A116A117A118A119A107A116A117A120A121A122A123A124A125A126A127A128A129A130A131A112A113A132A133A120A121A134A135A106A136A137A138A139A140A141A139A142A143A144A145A146A147A148A149A150A151A123A152A118A153A154A155A120A121A156A157A112A113A158A136A159A160A161A160A161A162A163A164A165A166A164A165A167A168A169A170A168A169A171A172A173A174A173A174A171A172A175A176一车牌识别的研究背景及现状分析（一）研究背景A177A178A179A180A181A182A183A184A185A186A187A188A189A190A183A191A192A193A194A195A196A197A198A183A199A200A186A180A201A202A203A194A195A204A205A206A207A208A190A209A210A211A212A203A213A214A215A216A217A186A202A218A219A194A195A220A209A194A195A221A222A223A224A225A226A227A228A229A230A231A232A233A234A235A236A237A238A194A195A204A205A239A240A232A241A242A243A244A245A246A194A195A204A205A247A248A232A249A250A243A251A252A253A254A255A29A0A1A2A3A4A254A255A5A6A7A8A9A10A11A12A13A14A15A16A17A5A18A19A49A51A20A21A22A23A53A24A25A5A17A26A27A28A30A31A60A254A255A32A5A33A34A18A19A35A36A37A38A49A21A22A23A254A255A39A40A41A42A43A5A44A45A46A47A254A255A31A75A41A48A50A52A54A55A56A44A45A57A58A84A85A59A46A47A84A87A88A89A61A54A62A47A84A1A2A63A44A62A47A64A65A66A33A67A5A68A69A32A254A255A49A75A51A20A70A71A72A73A74A76A5A77A78A32A31A106A71A72A79A80A5A110A81A82A81A65A49A53A8A9A83A86A5A90A91A92A31A118A71A72A106A81A119A93A94A123A95A96A97A121A98A5A118A99A30A32A119A31A124A100A0A101A102A11A103A104A73A25A21A22A23A71A72A254A255A32A5A11A6A7A105A107A49（二）现状A108A109A111A112A113A114A126A115A116A128A117A120A122A125A127A129A130A131A132A111A136A128A117A133A134A111A139A135A137A138A140A141A144A142A143A145A140A141A148A146A147A149A150A151A152A153A154A155A156A128A117A157A158A111A160A159A161A162A114A163A164A165A166A167A168A169A96A97A170A171A114A172A173A174A125A175A151A152A176A177A178A179A180A151A152A166A181A182A123A95A96A97A183A175A151A152A114A184A185A186A187A188A189A190A111A191A192A193A127A166A194A167A195A196A197A198A114A199A200A177A201A202A197A168A169A203A204A114A123A95A205A96A97A151A152A111A139A135A206A207A111A96A97A208A157A183A175A209A210A211A177A183A175A212A185A186A213A214A176二、系统构成A215A216A217A218A219A220A221A215A222A219A223A224A225A226A227A228A229A230A228A231A215A220A216A232A225A217A233A234A235A236A237A238A239A240A217A219A241A215A242A239A243A244A245A246A247A248A215A216A233A249A250A251A252A253A254A225A221A215A255A6A228A215A216A3A0A225A217A233A228A215A216A255A6A225A142A1A2A4A5A7A228A216A232A8A9A225A10A11A2A12A254A228A216A232A13A14A225A15A16A17A18A19A20A21A22A37A23A24A25A26A27A28A29A30A31A60A218A32A33A34A35。A36A221A38A39A40A41A42A43A44A45A36三、设计步骤A46A47A48A49A50A51A52A53A54A55A56A57A224A58A59A61A62A63A64A65A66A67A68A46A47A69A70A71A56A72A73A46A47A74A75A76A56A72A71A46A47A74A75A48A49A77（一）、预处理及边缘提取一般情况下，采集到的图像有由于光线过强，或者偏弱都会不理想的情况，这些都会对后续的图像处理产生影响。以及车速的不稳定等因素都会不同程度地影响图像效果，出现模糊、歪斜和缺损等严重缺陷，车牌字符边界模糊、细节不清、笔画断开、粗细不均等现象，从而影响车牌区域分割与字符识别的工作，所以识别前需要对原始图象进行预处理。A78A225A79A80A81A82A83A84A85A86A87A88A781、图象的采集与转换现有牌照的字符与背景的颜色搭配一般有蓝底白字、黄底黑字、白底红字、绿底白字和黑底白字等输入车牌图象灰度校正平滑处理提取边缘A226A89A78A90A79A80A81A91A92A93A94A95A96A97A98A226A99A100A101A102A103A104A95A96A105A106A107A108A109A110A111A112A113G1972G12193，G2045G11004不同的色G5437G17902G17959G4613G2499以G4570区域与背景G7138G7186地区分出G7481，G1375G3926，对蓝底白字这G12193G7380G5132G16277的牌照，采G11004蓝色G37G17902G17959G7114牌照区域G1038一G1154的G11709G5430，而牌照字符G3324区域G1025G5194不G2588现。因G1038蓝色G708G21G24G24，G19，G19与白色G708G21G24G24，G21G24G24，G21G24G24G709G3324G37G17902G17959G1025G5194G7092区分，而G3324G42、G53G17902G17959或G7171灰度图象G1025G5194G7092G8504G1427G2045。同理对白底黑字的牌照G2499G11004G53G17902G17959，绿底白字的牌照G2499以G11004G42G17902G17959G4613G2499以G7138G7186G2588现出牌照区域的G1313G13634，G1427于后续处理。原图、灰度图及G1866G11464G7053图G16277图G21与图G22。对于G4570G5437色图象G17728G6454G6116灰度图象G7114，图象灰度G1552G2499由下G19766的G1856G5347G16757G12651G726G0110B0588G0302RG7081G709G3RGBG7082G709A114A227A114A1152、边缘提取边缘G7171G6363图像G4628G18108G1154度G2476G2282G7186G14891的G18108分，G7171图像G20130、G13453理G10317G5461提取和G5430G10378G10317G5461提取等图像分G7524的重要G3534G11796。所以G3324G8504G6117G1216要对图像进行边缘G7828G8991。图象G3698强处理对图象牌照的G2499G17789G16760度的G6925G2904和G12628G2282后续的牌照字符定G1313和分割的G19602度都G7171G5468有G5529要的。G3698强图象对G8616度度的G7053G8873有G726灰度线G5627G2476G6454、图象平滑处理等。G7081G709灰度校正由于牌照图象G3324G6305G6680G7114G2475到G12193G12193G7477G1226的G19492G2058和G5190G6212，图象的灰度G1552G5460G5460与G4466G19481景G10301不G4448G1852G2317配，这G4570G11464G6521影响到图象的后续处理。G3926果G17908G6116这G12193影响的原因G1039要G7171由于G15999G6680G10301G1319的G17840G17829不同，G1363G5483图象G1025G3842区域和边缘区域的灰度G3845G15925，或G7171由于G6680像G3848G3324G6207G6563G7114G2520G9869的G9801G6947度有G17751G3835的G5058G5334而产生图象灰度G3845G11507，或G7171由于G7345光不G17287而G1363G5483图像的灰度G2476G2282范围G5468窄。这G7114G4613G2499以采G11004灰度校正的G7053G8873G7481处理，G3698强灰度的G2476G2282范围、丰富灰度层次，以达到G3698强图象的对G8616度和分辨率。G6117G1216发现车辆牌照图A116A117A118A119A120A121A122象的灰度取G1552范围G3835多G4628G19492G3324R50,200之间，而且总G1319上灰度偏低，图象G17751暗。根据图象处理系统的G7477G1226，G7380好G4570灰度范围展开到S0,255之间，G1038G8504G6117G1216对灰度G1552作G3926下的G2476G6454G726STRRRMIN,A123RMAXG1363G5483SSMIN,SMAX,G1866G1025，TG1038线G5627G2476G6454G726MINMAXMINMAXMAXMINMINMAXMINMAXRRRSRSRRRSSSG708G22若RG24G19,G21G19G19、SG19，G21G24G24则G72685R7115050255R150255SG7084A124A125A126A127A128A129A130A131A124A132A126A127A133A134A135A136A124A137G7082G709平滑处理对于G2475噪声G5190G6212严重的图象，由于噪声G9869多G3324频域G1025映射G1038高频分量，因G8504G2499以G3324G17902过低A138A139A140A141A143A144A145G17902滤波器G7481滤除噪声，但G4466G19481G1025G1038了G12628G2282G12651G8873，也G2499以G11464G6521G3324空域G1025G11004求邻域平均G1552的G7053G8873G7481削弱噪声的影响，这G12193G7053G8873称G1038图象平滑处理。G1375G3926，某一象素G9869的邻域S有两G12193表示G7053G8873G7268邻域和4邻域分别对应的邻域平均G1552G1038，A124A146A147A148A149A150A151A152A148A149A150A153SJIJIFMJIG,1,G708G24G709G1866G1025，MG1038邻域G1025除G1025心象素G9869FI,J之外包括的G1866它象素总数，对于4邻域M4，8邻域M8。然而邻域平均G1552的平滑处理会G1363G5483图象灰度急剧G2476G2282的地G7053，尤G1866G7171G10301G1319边缘区域和字符轮廓等G18108分产生模糊作G11004。G1038了克服这G12193平均G2282引起的图象模糊现象，G6117G1216给G1025心G9869象素G1552与G1866邻域平均G1552的G5058G1552设G13634一固定的阈G1552，只有G3835于该阈G1552的G9869才能替G6454G1038邻域平均G1552，而G5058G1552不G3835于阈G1552G7114，仍保留原G7481的G1552，从而减少由于平均G2282引起的图象模糊。边缘提取G7171G17751经典的G12651G8873，G8504处边缘的提取采G11004的G7171G53OBERTSG12651子。A154A155A156A157A158A159A160综上所述，结合MATLAG37G4466验过程，G5483出不G7171每一G12193图像处理之初都适合滤波和边界G3698强。本次汽车车牌的识别，G1038了保存更多的有G11004信息，经过多次G8616G17751，选择图9作G1038后期处理的依据。（二）、牌照的定位和分割牌照的定G1313和分割G7171牌照识别系统的关键技术之一，G1866G1039要G11458的G7171G3324经图象预处理后的原始灰度图象G1025G11842定牌照的G1867G1319G1313G13634，G5194G4570包G2559牌照字符的一G3371子图象从G6984G1022图象G1025分割出G7481，G1391字符识别子系统识别之G11004，分割的G1946G11842与G2554G11464G6521关系到G6984G1022牌照字符识别系统的识别率。由于牌照图象G3324原始图象G1025G7171G5468有G10317G5461的一G1022子区域，G11842G2011G16840G7171G8712平度G17751高的G8190G2533G17829G1296的G19283G7053G5430，它G3324原始图象G1025的G11468对G1313G13634G8616G17751集G1025，而且G1866灰度G1552与G2620边区域有G7138G7186的不同，因而G3324G1866边缘G5430G6116了灰度G12373G2476的边界，这G7691G4613G1427于G17902过边缘G7828G8991G7481对图象进行分割。4G22G21G24I,JG20G25G268G21G22I,JG204A161A162A163A164A165A166A167A168A169A170A171A172A173A174A175A176A177A178A179A1681、牌照区域的定位牌照图象经过了以上的处理后，牌照区域G5062经G2325分G7138G7186，而且G1866边缘G5483到了G2258G2214和G2164强。G8504G7114G2499进一G8505G11842定牌照G3324G6984G5145图象G1025的G1946G11842G1313G13634。这G18336选G11004的G7171数G4410G5430G5589G4410的G7053G8873，G1866G3534本G5617想G7171G11004G1867有一定G5430G5589的G7438G7512G1815素G2447量度和提取图像G1025的对应G5430G10378以达到对图像分G7524和识别的G11458的。数G4410G5430G5589G4410的应G11004G2499以G12628G2282图像数据，保G6357它G1216G3534本的G5430G5589G10317G5461，G5194除G2447不G11468G5190的结G7512。G3324本程G5219G1025G11004到了G14204G13972和G19393合这两G1022G3534本G17828G12651，G7380后G17836G11004了BG90G68REG68OG83EG81G7481G2447除对象G1025不G11468G5190的G4579对象。A168A169A169A180A181A182A183A184A183A185A186A187A188A183A184A189A190A191A183A185A192A193A194A195A196A197A198A199A194A195A182A183A1842、牌照区域的分割对车牌的分割G2499以有G5468多G12193G7053G8873，本程G5219G7171G2045G11004车牌的G5437色信息的G5437色分割G7053G8873。根据车牌底色等有关的G1820验G11705识，采G11004G5437色像素G9869统G16757的G7053G8873分割出合理的车牌区域，G11842定车牌底色蓝色G53G42G37对应的G2520G14270灰度范围，然后行G7053G2533统G16757G3324G8504颜色范围G1881的像素G9869数量，设定合理的阈G1552，G11842定车牌G3324行G7053G2533对图像进行G14116G15444G2447除G7446G17148G17902过G16757G12651G4559G6226X和YG7053G2533车牌的区域G4448G6116车牌定G1313对分割出的车牌G1582进一G8505处理A200A201A202A203A204A205A206的合理区域。然后，G3324分割出的行区域G1881，统G16757G2027G7053G2533蓝色像素G9869的数量，G7380G13468G11842定G4448G6984的车牌区域A207A208A209A210A211A212A213A214A215A216A217A219A220A222A223A228A229A230G22、车牌进一G8505处理经过上述G7053G8873分割出G7481的车牌图像G1025存G3324G11458G7643G10301G1319、背景G17836有噪声，要想从图像G1025G11464G6521提取出G11458G7643G10301G1319，G7380G5132G11004的G7053G8873G4613G7171设定一G1022阈G1552T，G11004TG4570图像的数据分G6116两G18108分G726G3835于T的像素G13688和G4579于T的像素G13688，G2375对图像G1120G1552G2282。均G1552滤波G7171典G3423的线G5627滤波G12651G8873，它G7171G6363G3324图像上对G11458G7643像素给一G1022模G7507，该模G7507包括了G1866G2620围的G1032G17829像素。G1889G11004模G7507G1025的G1852G1319像素的平均G1552G7481G1207替原G7481像素G1552。A207A208A231A232A233A222A223A228A229A230A228A234A235A236A237A238A239A240A207（三）、字符的分割与归一化A241A242A243A244A245A246A247A248A249A250A251A252A253A241MA254NSIZEA255DA66A254A67A0A1A2A3A4A3A5A6A7A8A9A254A77A101JN1A254A79A241A7A15A11SA255JA660A254A81A12A247A254A83A13A241A7A15A11A14A16A17A18A246A12A247A83A241A7A82A19A14A16A17A18A246A90A20A241A7A17A21A22A254A77A10A250A23A24A254A1A69A241A7A17XA97A254A79A25A26A27A28A29A250A23A24A81A12A247A254A246A37A30A31A32A244A245A62A33A34A35A36A38A39A40A41A42A43A44A40A45A46A474020A64A61A48A49A50A41A42A43A44A40A45A46A51A52A53A54A55A56A57A58A59A601、字符分割G3324汽车牌照G14270G2172识别过程G1025，字符分割有G6227前G2563后的作G11004。它G3324前期牌照定G1313的G3534G11796上进行字符的分割，然后G1889G2045G11004分割的结果进行字符识别。字符识别的G12651G8873G5468多，因G1038车牌字符间间G19560G17751G3835，不会出现字符G12908G17842情况，所以G8504处采G11004的G7053G8873G1038G4559G6226G17842续有G7003字的G3371，若G19283度G3835于某阈G1552，则G16760G1038该G3371有两G1022字符G13464G6116，需要分割。A43A63A65A68A36A38A39A40A70A71A41A42A43A442、字符归一化一般分割出G7481的字符要进行进一G8505的处理，以G9397G17287下一G8505字符识别的需要。但G7171对于车牌的识别G5194不需要G3838多的处理G4613G5062经G2499以达到正G11842识别的G11458的。G3324G8504只进行了G5414一G2282处理，然后进行后期处理A43A63A72A73A74A75A76A78A80A84A85A86A87A88A89A91（四）、字符的识别字符的识别G11458前G11004于车牌字符识别G50G38G53G1025的G12651G8873G1039要有G3534于模G7507G2317配的G50G38G53G12651G8873以及G3534于G1166工G12082经G13605G13488的G50G38G53G12651G8873。G3534于模G7507G2317配的G50G38G53的G3534本过程G7171G29G20330G1820对G5465识别字符进行G1120G1552G2282G5194G4570G1866G4622G4556G3835G4579G13565G6930G1038字符数据G5223G1025模G7507的G3835G4579，然后与所有的模G7507进行G2317配，G7380后选G7380G1351G2317配作G1038结果。G11004G1166工G12082经G13605G13488进行字符识别G1039要有两G12193G7053G8873G29一G12193G7053G8873G7171G1820对G5465识别字符进行G10317G5461提取，然后G11004所G14731G5483的G10317G5461G7481G16769G13463G12082经G13605G13488分G12879器。识别效果与字符G10317G5461的提取有关，而字符G10317G5461提取G5460G5460G8616G17751G13803G7114。因G8504，符G10317G5461的提取G4613G6116G1038G11752G12362的关键。G2490一G12193G7053G8873则G1817分G2045G11004G12082经G13605G13488的G10317G9869，G11464G6521G6238G5465处理图像输入G13605G13488，由G13605G13488G14270G2172G4466现G10317G5461提取G11464G14279识别。模G7507G2317配的G1039要G10317G9869G7171G4466现G12628G2345，G5415字符G17751G16280G6984G7114对字符图像的缺损、G8757G17869G5190G6212适应G2159强且识别率G11468G5415高。综合模G7507G2317配的这些G1260G9869G6117G1216G4570G1866G11004G1038车牌字符识别的G1039要G7053G8873。模G7507G2317配G7171图象识别G7053G8873G1025G7380G1867G1207表G5627的G3534本G7053G8873之一，它G7171G4570从G5465识别的图象或图象区域FI,JG1025提取的若G5190G10317G5461量与模G7507TI,JG11468应的G10317G5461量G17892G1022进行G8616G17751，G16757G12651它G1216之间G16280G7696G2282的G1126G11468关量，G1025G1126G11468关量G7380G3835的一G1022G4613表示期间G11468G1296程度G7380高，G2499G4570图象G5414于G11468应的G12879。也G2499以G16757G12651图象与模G7507G10317G5461量之间的G17329G12175，G11004G7380G4579G17329G12175G8873G2040定所G4658G12879。然而，G17902G5132情况下G11004于G2317配的图象G2520G14270的G6116像G7477G1226存G3324A92A93A94A95A96A98A99G5058G5334，产生G17751G3835的噪声G5190G6212，或图象经预处理和G16280G7696G2282处理后，G1363G5483图象的灰度或像素G9869的G1313G13634发生G6925G2476。G3324G4466G19481设G16757模G7507的G7114G1517，G7171根据G2520区域G5430G10378固有的G10317G9869，G12373出G2520G12879G1296区域之间的G5058别，G5194G4570G4493G7143由处理过程引起的噪声和G1313移等因素都考虑进G2447，按照一些G3534于图象不G2476G10317G5627所设G16757的G10317G5461量G7481G7512建模G7507，G4613G2499以避免上述问题。A100A101A102A103A104A105A106A107A108A100G8504处采G11004G11468减的G7053G8873G7481求G5483字符与模G7507G1025哪一G1022字符G7380G11468G1296，然后G6226到G11468G1296度G7380G3835的输出。汽车牌照的字符一般有七G1022，G3835G18108分车牌第一G1313G7171汉字，G17902G5132G1207表车辆所G4658省份，或G7171军G12193、警别等有G10317定G2559义的字符G12628称；紧G6521G1866后的G1038字母与数字。车牌字符识别与一般G7003字识别G3324于它的字符数有G19492汉字共约G24G19多G1022，G3835写英G7003字母G21G25G1022，数字G20G19G1022。所以建立字符模G7507G5223也极G1038G7053G1427。G1038了G4466验G7053G1427结合本次设G16757所选汽车牌照的G10317G9869，只建立了4G1022数字G21G25G1022字母与G20G19G1022数字的模G7507。G1866他模G7507设G16757的G7053G8873与G8504G11468同。G20330G1820取字符模G7507，G6521着依次取G5465识别字符与模G7507进行G2317配，G4570G1866与模G7507字符G11468减，G5483到的0越多那么G4613越G2317配。G6238每一G5145G11468减后的图的0G1552G1022数保存，然后G6226数G1552G7380G3835的，G2375G1038识别出G7481的结果。A100A111A109A105A106A110A112A114A113A115A116A105A106A117A118A119A120A121A122A123A124A125A126A117A103A127A128A129A103A104A130A131A132A133A117A134A103A131A132A135A136A137A138A127A139A129A103A104A130A131A132A133A117A103A140A131A132A135A136A137A138A141A105A106A103A104A130A131A132A103A104A142A143A144A145A146A147A142A148A149A146A150A144A151A152A153A147A117A128A129A154A155A137A138A117A153A156A117A105A106A157A158A144A159A125A160A131A132A161A162A145A1635A129A103A104A130A131A132A133A117A103A140A130A164A103A131A132A135A136A137A138A92A93A94A95A96A98A99三、设计结果及分析原始图像G29预处理后G726车牌定G1313和提取G726字符的分割G726图像识别G726G17902过以上G6117G1216G2499以看出，该G7053G8873对图像进行G7828G8991G1867有G17751好的识别效果。G6984G1022过程G11004MATLAG37语言编程G4466现，G7092G7114间滞后感，G2499以G9397G17287G4466G7114G7828出的要求。但G7171G3324设G16757的过程G1025发现，G1363G11004G2490一G5145图像后，识别效果始G13468没有那么理想。需要G1582一定的设G13634后才能识别出G11468应的字符。对于识别错误情况的分G7524A165A166A167A168A169A170A171G2499G11705，G1039要原因G726一G7171牌照G14270身的G8757渍等影响了图象的G17148量；G1120G7171牌照字符的分割G3845败导致的识别错误；G1889G4613G7171G18108分字符的G5430G10378G11468G1296G5627，G8616G3926，G37和8；A和4等字符识别结果G2499能发生混淆的情况。G3324车牌识别的过程G1025数字G5223的建立也G5468重要,只有数字G5223的G1946G11842才能保证G7828G8991出G7481的数据正G11842。G2011割出G7481的数据要与数据G5223的数据作G8616G17751，所以数据G5223的数据尤G1038重要。总之，尽管G11458前牌照字符的识别率G17836不理想，但G7171只要G3324分割出的字符的G3835G4579、G1313G13634的G5414一G2282，以及尝试提取分G12879识别能G2159更好的G10317G5461G1552和设G16757分G12879器等环节上G1889G4448G2904，进一G8505提高识别率也G7171G2499行的。四、总结G4466验对车牌识别系统的软G1226G18108分进行了G11752G12362，分别从图像预处理、车牌定G1313、字符分割以及字符识别等G7053G19766进行了系统的分G7524。G3324车辆牌照字符识别系统的G11752G12362领域，G17829G1972年出现了许多G2011G4466G2499行的识别技术和G7053G8873，从这些新技术和G7053G8873G1025G2499以看到两G1022G7138G7186的趋势G726一G7171G2345一的预处理和识别技术都G7092G8873达到理想的结果，多G12193G7053G8873的有G7438结合才能G1363系统有效识别能G2159提高。G3324本系统的设G16757G7114，也汲取了以上一些G12651G8873的G5617想，结合G4466G19481，反复G8616G17751，综合分G7524；G1120G7171G3324有效G5627和G4466G11004的原则下，结合G12082经G13605G13488和G1166工智能的新技术的应G11004G7171G11752G12362的一G1022G7053G2533。G1889者根据车牌G10317G9869，一般采G11004的车牌定G1313G12651G8873有边缘G7828G8991定G1313G12651G8873，G8712平G7053G2533灰度G2476G2282G7053G8873，G3534于G5437色G10317G5461的车牌定G1313G7053G8873，G5430G5589滤波，G12082经G13605G13488G8873等。这G18336G6117采G11004的G7171边缘G7828G8991的G7053G8873G4466现定G1313的。本设G16757虽然只对蓝底白字车牌进行分割识别，对黑底白字车牌原则上G6984G1022G12651G8873G2499G11464G6521适G11004，对白底黑字车牌、黄底黑字车牌，需要对车牌定G1313G12651G8873进行调G6984，G5194G4570图像反G17728G708G19G2476G20、G20G2476G19G709，而车牌