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Information Technology Journal
  Year: 2012 | Volume: 11 | Issue: 11 | Page No.: 1605-1611
DOI: 10.3923/itj.2012.1605.1611
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Image Copy Detection Based on a Similar-sector Model and DFT

Ying Zheng and Yaping Lin

To protect authorized digital images from illegal use, image copy detection is very important for copyright protection. Its key issue is to extract robust feature to detect images with variety of attacks. In this study, a robust algorithm based on a similar-sector model and Discrete Fourier Transform (DFT) is proposed. An image is first divided by 48 concentric ellipses and 48 similar-sectors as the similar-sector model does, then 1D DFT magnitude spectrum which is obtained from the pixel gray values in each elliptical ring, is used as our image feature for copy detection. Our feature is not only robust to various signal modifications but also to geometric distortions. At last, the correlation coefficient is calculated to measure the similarity between the test image and the original image. The experimental results demonstrate that the proposed approach outperforms the existing methods and performs particularly well on detecting geometric distorted images, for instance, it can detect the image which is scaled, cut or rotated to any degree.
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How to cite this article:

Ying Zheng and Yaping Lin, 2012. Image Copy Detection Based on a Similar-sector Model and DFT. Information Technology Journal, 11: 1605-1611.

DOI: 10.3923/itj.2012.1605.1611






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