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1、东华理工大学硕士学位论文东华理工大学研究生毕业论文英文摘要首页用纸THESIS：FeatureExtractionofPointCloudDataBasedonRANSACSPECIALIZATION:GeomaticsEngineeringPOSTGRADUATE:YouJun-fuMENTOR:GuanYun-lanAbstractFeatureextractionfrompointclouddata,havemanyimportantapplicationsinthefieldofcomp
2、utervision,patternrecognition,city,geologyandotherprofessionals.Featurepointsinpointclouddata,asthebasictextureandgeometricmotifscharacteristicfeatures,arenotduetochangeindifferentcoordinatesystem.Sincethebirthofthethree-dimensionallaserscanning,itma
3、kesthepointclouddatahaveanewlife,andhowtoextractfeaturepointsfrompointclouddatahasbecomeahotresearchdirection.Thebasicelements,point,line,surface,body,etc.,asafundamentalpartofthepointclouddata,andextractingtheseinterestedelementshavemanyresearchachi
4、evements.Inthetwo-dimensionalimage,HoughTransform(HT)algorithmisanimportantmethodforextractingstraightlines,circles,etc.,HTalgorithmhasbeenshowntohavegoodrobustness.DrawingtheHoughTransformmethodintwo-dimensionalimage,the3D-HTbecomeafeasibleapproacht
5、oextractsurfacefeaturepointsfromthree-dimensionaldata.RANSACalgorithmisalsoacommonmethodoffeatureextractionformdata,anditreflectsgoodresultsandrobustnessinextractingregularobjectsfrompointclouddata.Theleastsquaresmethodanditsimprovedalgorithmsarealso
6、usedtodiscretedatapointsinthesurfacefittingandfeatureextraction.Thispaperfocuseson3D-HT,theleastsquaresmethodanditsimprovedalgorithm,RANSACalgorithmtoextractthepointsofplaneandspherefeatures,thendiscussesthedifferencesbetweenthem.Bycontrastdifferentt
7、hreemethods,RANSACalgorithmdemonstratedthesuperiority.Lastly,RANSACalgorithmwasusedtoextractfeaturepointsfromtwoactualpointcloud,andextractionresultswithGeomagicsimplecomparison,furthervalidationRANSACsuperiorityinpointcloudextraction.Keywords:PointC
8、loud;Three-dimensionalLaserScanning;FeatureExtraction;LeastSquares;3D-HT;RANSACII万方数据目录目录摘要..............................................................................................................................IAbstract........................
