Yazar "Avcibaş, Ismail" seçeneğine göre listele

Listeleniyor 1 - 3 / 3
  • Küçük Resim Yok
    Öğe
    Audio codec identification through payload sampling
    (2011) Hiçsönmez, Samet; Sencar, Hüsrev Taha; Avcibaş, Ismail
    W0065 present a new method for audio codec identification that does not require decoding of coded audio data. The method utilizes randomness and chaotic characteristics of coded audio to build statistical models that represent encoding process associated with different codecs. The method is simple, as it does not assume knowledge on encoding structure of a codec. It is also fast, since it operates on a block of data, which is as small as a few kilobytes, selected randomly from the coded audio. Tests are performed to evaluate the effectiveness of the technique in identification of the codec used in encoding on both singly coded and transcoded audio samples. © 2011 IEEE. © 2012 Elsevier B.V., All rights reserved.
  • Küçük Resim Yok
    Öğe
    Classification of audio codecs based on coding characteristics
    (2012) Hiçsönmez, Samet; Sencar, Hüsrev Taha; Avcibaş, Ismail
    We propose a fast, simple and new method for identification of audio codecs that does not require decoding of coded audio data. The method uses chaotic and randomness features of coded audio to build models associated with different codecs. The most important features of the method are operating on just a few kilobytes of data sampled randomly from audio file and assuming no knowledge on encoding structure of a codec. These two features make it fast and simple. Experiments are performed on both singly coded and transcoded audio samples to measure accuracy of the technique. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.
  • Küçük Resim Yok
    Öğe
    Image manipulation detection using contourlet transform
    (2012) Özparlak, Levent; Avcibaş, Ismail
    In this paper, we use contourlet transform for digital image manipulation detection. We extract contourlet and wavelet features and test these obtained features on a controlled image data set. Results show that contourlet based features gives better success rates than wavelet based ones. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.