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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Min-Jen Tsai Cheng-Liang Lai Jung Liu |
| Copyright Year | 2007 |
| Description | Author affiliation: Inst. of Inf. Manage., Nat. Chiao Tung Univ., Hsinchu (Min-Jen Tsai) |
| Abstract | Digital forensics has lately become one of the very important applications to identify the characteristics and the originality of the digital devices. This study has focused on analyzing the relationship between digital cameras and the photographs by using the support vector machine (SVM). Based on the fact that the internal imaging formation algorithms of the cameras are different from one manufacturer to another, our approach first calculates the characteristic values of the images taken by different cameras in conjunction with image processing techniques and data exploration methods. The training and categorization procedures of the image characteristic values are further conducted through SVM to identify the source camera of the images. Based on SVM's ability to distinguish cameras of different brands, this study also examines whether the method can differentiate cameras of the same brand, or even the popular mobile phones with camera. The experiment results demonstrate that our approach can achieve higher identification rate for camera and mobile phone sources than the results from other literatures. |
| File Size | 3058494 |
| File Format | |
| ISBN | 1424407273 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2007.366212 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-04-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Digital cameras Mobile handsets Digital forensics Support vector machines Color Manufacturing processes Digital images Image converters Humans Frequency domain analysis feature extraction cameras correlation |
| Content Type | Text |
| Resource Type | Article |
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