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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Image feature extraction using compressive sensing

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      Author(s)
      Eleyan, A.
      Köse, Kıvanç
      Çetin, A. Enis
      Date
      2014
      Source Title
      Image Processing and Communications Challenges 5
      Print ISSN
      2194-5357
      Publisher
      Springer
      Volume
      233
      Pages
      177 - 184
      Language
      English
      Type
      Conference Paper
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      Abstract
      In this paper a new approach for image feature extraction is presented. We used the Compressive Sensing (CS) concept to generate the measurement matrix. The new measurement matrix is different from the measurement matrices in literature as it was constructed using both zero mean and nonzero mean rows. The image is simply projected into a new space using the measurement matrix to obtain the feature vector. Another proposed measurement matrix is a random matrix constructed from binary entries. Face recognition problem was used as an example for testing the feature extraction capability of the proposed matrices. Experiments were carried out using two well-known face databases, namely, ORL and FERET databases. System performance is very promising and comparable with the classical baseline feature extraction algorithms.
      Keywords
      Measurement matrix
      Compressed sensing
      Face image
      Face recognition
      Feature extraction
      Signal reconstruction
      Vector spaces
      Permalink
      http://hdl.handle.net/11693/26986
      Published Version (Please cite this version)
      http://dx.doi.org/10.1007/978-3-319-01622-1_21
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      • Department of Electrical and Electronics Engineering 3702
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