基于Matlab的手背静脉图像特征提取VIP免费

第I页基于Matlab的手背静脉图像特征提取摘要人体手背静脉识别技术作为一种全新的非接触式生物特征识别技术，与以往传统的指纹以及虹膜识别技术相比表现出了许多明显的优势，近年来得到了广泛的关注。手背静脉识别是通过分析手背上的静脉特征来进行身份识别的。首先对手背静脉图像预处理，得到细化图像，利用分割思想把细化图像分割为多个子图像，然后分别提取平均原点静矩，组合成特征向量，最后再结合最近邻法，用最小欧氏距离的方法来进行匹配，实验结果验证了该方法的有效性和可行性。关键词：静脉识别，原点静距，特征提取，匹配TheFeatureExtractionoftheHandVeinImageBasedonMatlabAuthor：CaiHongshanTutor：CaiChaofengI第II页ABSTRACTWiththearrivalofinformationage,informationsecurityhasbecomeincreasinglyimportant.Manyoccasionsneedtoidentifytheirvisitorsandbiometricidentificationtechnologyhasprovidedeffectivesolutionstosuchproblems.Asanewnon-contactBiometricidentificationtechnology,handveinverificationtechnologyhasmanyobviousadvantagescomparedwiththetraditionalfingerprintandirisrecognitiontechnologyandhasreceivedattentionwidely.Humanhandveinrecognitiontechnologycanimprovethereliabilityofidentityresolutioninvirtueofveinfeatureonthebackofthehand.Basedontheresearchandanalysisoftherecentbiometricidentificationtechnologyresearchresults,thispaperconductsdeepresearchonsomeofthekeytechnologiesofthehandveinrecognitiontechnology,especiallyonfeatureextractionandfeaturematching.Inthefeatureextractionstage,thispaper’salgorithmbasedonthinnedveinimagetakesoriginstaticmomentasrecognitionfeatures.Wecangettherefiningimagethroughthepreprocessingofthehandveinimage,dividetherefiningimageintomultiplesub-images,extracttheaverageoriginstaticmomentintothefeaturevector,usethesmallestEuclideandistancetomatchit.Theexperimentalresultverifiestheeffectivenessandfeasibilityofthemethod.KEYWORDS:VeinVerification,originstaticmoment,featureextractionII第III页目录1绪论.....................................................................................................................................11.1生物特征识别技术简介...........................................................................................11.2手背静脉识别技术.................................................................................................31.3手背静脉特征提取与匹配研究现状.......................................................................41.4论文主要内容与结构.............................................................................................62手背静脉图像的预处理....................................................................................................82.1图像的有效区域提取.............................................................................................82.2图像的归一化.........................................................................................................92.3图像的增强...........................................................................................................102.4图像的分割.............................................................................................................112.5图像的细化...........................................................................................................122.6本章小结...............................................................................................................123手背静脉图像的特征提取与匹配................................................