一级黄色片免费播放|中国黄色视频播放片|日本三级a|可以直接考播黄片影视免费一级毛片

高級(jí)搜索

留言板

尊敬的讀者、作者、審稿人, 關(guān)于本刊的投稿、審稿、編輯和出版的任何問(wèn)題, 您可以本頁(yè)添加留言。我們將盡快給您答復(fù)。謝謝您的支持!

姓名
郵箱
手機(jī)號(hào)碼
標(biāo)題
留言內(nèi)容
驗(yàn)證碼

基于HMM和SVM的指紋分類方法

王崇文,  李見為,  陳為民

王崇文, 李見為, 陳為民. 基于HMM和SVM的指紋分類方法[J]. 電子與信息學(xué)報(bào), 2003, 25(11): 1488-1493.
引用本文: 王崇文, 李見為, 陳為民. 基于HMM和SVM的指紋分類方法[J]. 電子與信息學(xué)報(bào), 2003, 25(11): 1488-1493.
Wang Chongwen, Li Jianwei, Chen Weimin. Fingerprint classification using hmm and svm[J]. Journal of Electronics & Information Technology, 2003, 25(11): 1488-1493.
Citation: Wang Chongwen, Li Jianwei, Chen Weimin. Fingerprint classification using hmm and svm[J]. Journal of Electronics & Information Technology, 2003, 25(11): 1488-1493.

基于HMM和SVM的指紋分類方法

Fingerprint classification using hmm and svm

  • 摘要: 該文提出了指紋分類的一種新型方法:使用指紋編碼的基于隱馬爾可夫模型(HMM)和支持向量機(jī)(SVM)的兩級(jí)分類,該方法采用FingerCode作為指紋的特征表述,首先用5個(gè)偽二維 HMM進(jìn)行類別初選,確定最可能的兩種指紋分類結(jié)果,再用相應(yīng)的 SVM分類器做最終判決,實(shí)驗(yàn)表明,分類性能已經(jīng)達(dá)到或超過(guò)目前流行的指紋分類算法,具有一定的實(shí)用價(jià)值。
    Abstract: In this paper, a new classification method is proposed that is based on HMM and SVM using FingerCode. This technique uses FingerCode as representation of fingerprint, first, using five HMM classifiers to classify originally, furthermore, basing on the most possible two results of classification by HMM, the corresponding SVM classifier is selected to make final decision. Through experiments, the performance of this method reaches or exceeds many popular ones and has value to a certainty in practice.
    • HTML全文
  • 劉少聰,新指紋學(xué),合肥,安徽人民出版社,1984.10,25-121.[2]K.Karu,A.K.Jain,Fingerprint classification,Pattern Recognition,1996,29(3),389-404.[3]L. Hong, A. K. Jain, Classification of fingerprint images, 11th Scandinavian Conference on Image Analysis, June 7-11, Kangerlussuaq, Greenland, 1999, 33-50.[4]C.V. Kameshwar Rao, K. Black, Type classification of fingerprints: A syntactic approach, IEEE Trans. on Pattern Anal. and Machine Intell., 1980, 2(3), 223-231.[5]C.L. Wilson, G. T. Candela, C. I. Watson, Neural network fingerprint classification, J. Artificial Nerual Networks, 1993, 1(2), 203-228.[6]G.T. Candela, P. J. Grother, C. I. Watson, R. A. Wilkinson, C. L. Wilson, PCASYS: A patternlevel classification automation system for fingerprints, NIST Tech. Report NISTIR 5647, August,1995.[7]D. Maio, D. Maltoni, A structural approach to fingerprint classification, Proc. 13th ICPR, Vienna,August, 1996, 112-128.[8]R. Cappelli, D. Maio, D. Maltoni, Fingerprint classification based on multispace KL, Proc. Workshop on Automatic Identification Advances Technologies, Summit, NJ, October 1999, 117-120.[9]A. Senior, A hidden Markov model fingerprint classifier, Proc of the 31st Asilomar Conference on Signals, Systems and Computers, Washington, 1997, 306-310.[10]A.P. Fitz, R. J. Green, Fingerprint classification using hexagonal fast Fourier transform, Pattern Recognition, 1996, 29(10), 1587-1597.[11]A.K. Jain, S. Prabhakar, L. Hong, A multichannel approach to fingerprint classification, IEEE Trans. on Pattern Anal. and Machine Intell., 1999, 21(4), 348-359.[12]R. Cappelli, D. Maio, D. Maltoni, Combining fingerprint classifiers, First International Workshop on Multiple Classifier Systems, Cagliari, June 2000, 351-361.[13]G.L. Marcialis, F. Roli, P. Frasconi, Fingerprint classification by combination of fiat and structural approaches, AVBPA 2001, LNCS 2091, Tokyo, 2001, 241-246.[14]Rabiner L, A tutorial on hidden Markov models and selected application in speech recognition,Proc. IEEE, 1989, 77(3), 256-286.[15]V.N.Vapnik著,張學(xué)工譯,統(tǒng)計(jì)學(xué)習(xí)理論的本質(zhì),清華大學(xué)出版社,2000,第2章.
  • 加載中
計(jì)量
  • 文章訪問(wèn)數(shù):  2194
  • HTML全文瀏覽量:  116
  • PDF下載量:  869
  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2002-05-13
  • 修回日期:  2003-01-09
  • 刊出日期:  2003-11-19

目錄

    /

    返回文章
    返回