摘要
Inordertosolvetheproblemoflowrecognitionrateoftraditionalfeatureextractionoperatorsunderlow-resolutionimages,anovelalgorithmofexpressionrecognitionisproposed,namedcentralobliqueaveragecenter-symmetriclocalbinarypattern(CS-LBP)withadaptivethreshold(ATCS-LBP).Firstly,thefeaturesoffaceimagescanbeextractedbytheproposedoperatorafterpretreatment.Secondly,theobtainedfeatureimageisdividedintoblocks.Thirdly,thehistogramofeachblockiscomputedindependentlyandallhistogramscanbeconnectedseriallytocreateafinalfeaturevector.Finally,expressionclassificationisachievedbyusingsupportvectormachine(SVM)classifier.ExperimentalresultsonJapanesefemalefacialexpression(JAFFE)databaseshowthattheproposedalgorithmcanachievearecognitionrateof81.9%whentheresolutionisaslowas16×16,whichismuchbetterthanthatofthetraditionalfeatureextractionoperators.
出版日期
2017年06月16日（中国期刊网平台首次上网日期，不代表论文的发表时间）
