1、割模板匹配【中文摘要】近年來(lái)，隨著社會(huì)經(jīng)濟(jì)的發(fā)展和人們生活水平的提高，汽車數(shù)量急劇增加，給交通控制和車輛管理帶來(lái)很大的困難，智能交通系統(tǒng)的誕生緩解了交通壓力，車牌號(hào)碼是車輛的“身份”標(biāo)識(shí)。所以，車牌識(shí)別技術(shù)已成為智能交通系統(tǒng)中的重要組成部分。車輛識(shí)別基于圖像處理和模式識(shí)別理論，對(duì)含有車輛牌照的圖像進(jìn)行分析處理，從而確定牌照在圖像中的位置，并進(jìn)一步提取和識(shí)別出文本字符。本文從車牌定位、字符分割和字符識(shí)別三方面對(duì)車牌識(shí)別技術(shù)進(jìn)行了深入研究。首先，本文研究了車牌定位模塊。采用基于顏色信息和幾何特征的車牌定位算法直接對(duì)采集到的彩色車輛圖像進(jìn)行車牌的定位分割，完成車牌定位；其次，對(duì)定位分割出的彩色車牌圖

2、像進(jìn)行預(yù)處理，先后對(duì)車牌圖像進(jìn)行灰度化、傾斜校正、二值化、形態(tài)學(xué)處理以及去除車牌邊框和非字符區(qū)域的處理，得到僅包含車牌字符區(qū)域的二值化圖像，為車牌字符的分割做好準(zhǔn)備；再次，對(duì)車牌字符分割進(jìn)行研究，采用垂直投影法對(duì)車牌字符進(jìn)行分割處理，將車牌的七個(gè)字符分割出來(lái)，并作歸一化處理，使字符的大小相同，且與模板庫(kù)中的字符大小一致，為車牌字符的識(shí)別奠定了堅(jiān)實(shí)的基礎(chǔ)；最后，對(duì)分割出的車牌字符進(jìn)行識(shí)別，本文對(duì)傳統(tǒng)的模板匹配算法進(jìn)行改進(jìn)，并采用改進(jìn)的模板匹配算法對(duì)分割出的字符進(jìn)行識(shí)別，給出了改進(jìn)算法的詳細(xì)工作過(guò)程，并用MATLAB件對(duì)該算法進(jìn)行仿真實(shí)驗(yàn)，結(jié)果顯示該算法具有一定的適應(yīng)性和魯棒性。另外，本文最后采用

3、了MATLAB對(duì)算法進(jìn)行了仿真實(shí)現(xiàn)，并對(duì)該算法的有效性進(jìn)行測(cè)試。實(shí)驗(yàn)表明，大多數(shù)圖像都能夠得到預(yù)期的效果。【英文摘要】Inrecentyears,withthedevelopmentofthesocialeconomyandtheimprovementofthepeople'slivingstandards,thenumberofcarsincreasesdramatically,whichmakesitdifficulttocontrolandmanagethevehiculartraffic.Theemergeneeoftheintelligenttransortationsyst

4、emrelievesthetrafficpressure,andthenumberofthelicenseplatesisthe“identity”signofthevehicle,sothetechnologyofthelicenseplaterecognitionisanimportantcomponentoftheintelligenttransportationsystemLicenseplaterecognitionisbasedonthetheoryofimageprocessingandpatternrecognitiontlocatesthepositionofthelicen

5、seintheimagesbyanalyzingandprocessingtheimagesofthevehiclelicenseplates,andfurthermoreitextractsandidentifysthecharacters.Thispaperstudiesthetechnologyofthelicenseplaterecognitionfromthreeaspects,includingthelicenseplatelocation,charactersegmentationandcharacterrecognition.Firstly,thepaperstudiesthe

6、moduleoflicenseplates.Thismoduleaccomplishesthelicenseplatelocationbyadoptingthelicenseplatelocationalgorithmbasedoncolorinformationandgeometricfeatures.Secondly,thepaperpreprocessesthelocatedlicenseplateimages.Itadoptskindsofmethodstoprocessthelicenseplateimages,includingcolorplateimagegrayscale,ti

7、ltcorrection,binarization,morphologicalprocessing,theremovaloflicenseplateframesandtheprocessofnon-characterregions,andthenobtainsthebinarylicenseplateimagesonlycontainingcharacterregions,whichmakespreparationsforthecharacterssegmentation.Onceagain,thepaperstudiesthecharactersegmentation.Itsegmentst

8、hesevencharactersoflicenseplatebyprojectionalgorithm,andmakesthemhavethesamesizewiththecharactersintemplatelibrarybynormalizedprocessing,whichlaysasolidfoundationforthecharacterrecognition.Finally,thesegmentedlicenseplatecharactersarerecognizedinthepaper.Itadoptstheimprovedtemplatematchingalgorithmtorealizethecharactersidentification,andintroducestheimplementofthealgorithmindetail,andutilizestheMATLABtosimulatetheexperimentsofthealgorithm,theresultsshowthatthealgorithmhasacertainadaptabilityandrobustnessnadditi