Yazar "Avcibas, Ismail" seçeneğine göre listele

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    A Comparison of Wavelet Family of Transforms from Image Forensics Perspective
    (Turgut Ozal Univ, 2012) Ozparlak, Levent; Avcibas, Ismail
    In this study, we compare wavelet based transforms for the cases of different image forensics problems. We extract wavelet based features and make experiments for different problems. The results show that a mixture of wavelet based features give the best performance in each experiment. In the absence of such a classifier with mixed features, the best performing features were obtained from contourlet transform coefficients.
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    Audio codec identification from coded and transcoded audios
    (Academic Press Inc Elsevier Science, 2013) Hicsonmez, Samet; Sencar, Husrev T.; Avcibas, Ismail
    A novel technique is presented to identify the codec of a coded audio. The technique does not perform decoding, utilize any coding metadata, or assume information about the structure describing the bit stream format of a codec. The underlying idea of the technique is that the design choices governing the compression level, audio quality and complexity of a codec will reveal themselves on the coded audio. To exploit this, the technique samples 2-4 kilobytes of data from a coded audio and analyzes the randomness and chaotic nature of the sampled data to build statistical models that represent encoding process associated with different codecs. In experiments, we utilize 16 of the most popular audio codecs used for high quality audio compression and in PSTNs, cellular networks, and VoIP networks by setting encoding parameters of each codec to its most commonly used values. Results show that the codec of an encoded audio can be identified with an accuracy of more than 95 percent. Other experiments considering several transcoding scenarios were also performed. Those results show that the scheme can even discriminate the first encoder of a doubly-encoded audio with an accuracy range of around 80 to 90 percent or more as long as the second codec operates on higher bit rates than the first one. (C) 2013 Elsevier Inc. All rights reserved.
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    Differentiating Between Images Using Wavelet-Based Transforms: A Comparative Study
    (Ieee-Inst Electrical Electronics Engineers Inc, 2011) Ozparlak, Levent; Avcibas, Ismail
    We propose statistical image models for wavelet-based transforms, investigate their use, and compare their relative merits within the context of digital image forensics. We consider the problems of 1) differentiating computer graphics images from photographic images, 2) source camera and source scanner identification, and 3) source artist identification from digital painting samples. The features obtained from ridgelet and contourlet transform-based image models almost always perform better than the features obtained from wavelet-based image models for the problems at hand. We outline properties of efficient image representation, relate these properties to wavelet-based transforms, and discuss the experimental results in relation to the model properties.