| Nonnegative matrix factorization with Log Gabor wavelets for image representation and classification |
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| 引用本文： | Zheng Zhonglong & Yang JieInst. of Image Processing and Pattern Recognition of Shanghai Jiaotong Univ.,Shanghai 200030,P. R. China. Nonnegative matrix factorization with Log Gabor wavelets for image representation and classification[J]. 系统工程与电子技术(英文版), 2005, 16(4) |
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| 作者姓名： | Zheng Zhonglong & Yang JieInst. of Image Processing and Pattern Recognition of Shanghai Jiaotong Univ. Shanghai 200030 P. R. China |
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| 作者单位： | Zheng Zhonglong & Yang JieInst. of Image Processing and Pattern Recognition of Shanghai Jiaotong Univ.，Shanghai 200030，P. R. China |
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| 摘 要： | 1.INTRODUCTION Inpatternanalysisandcomputervision,visualrecog nitionofobjectsisoneofthemostchallengingprob lems.Approachestoovercomesuchproblemshavefo cusedonusingseveralmethodologies.Appearance basedrepresentationandrecognitionisoneofthe mostsuccessfullyusedtoday.Itinvolvespreprocess ingofmultidimensionalsignals,suchasimagesof facesandcharactersorspectrogramsofspeech.In fact,thecoreofthepreprocessingisthesocalleddi mensionalityreduction.Thedimensionalityreductionaimstocompress thehighdi…
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Non-negative matrix factorization with Log Gabor wavelets for image representation and classification |
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| Zheng Zhonglong,Yang Jie. Non-negative matrix factorization with Log Gabor wavelets for image representation and classification[J]. Journal of Systems Engineering and Electronics, 2005, 16(4) |
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| Authors: | Zheng Zhonglong Yang Jie |
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| Affiliation: | Inst. of Image Processing and Pattern Recognition of Shanghai Jiaotong Univ., Shanghai 200030, P. R. China |
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| Abstract: | Many problems in image representation and classification involve some form of dimensionality reduction. Nonnegative matrix factorization (NMF) is a recently proposed unsupervised procedure for learning spatially localized, partsbased subspace representation of objects. An improvement of the classical NMF by combining with LogGabor wavelets to enhance its partbased learning ability is presented. The new method with principal component analysis (PCA) and locally linear embedding (LLE) proposed recently in Science are compared. Finally, the new method to several real world datasets and achieve good performance in representation and classification is applied. |
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| Keywords: | nonnegative matrix factorization (NMF) Log Gabor wavelets principal component analysis locally linear embedding (LLE) |
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