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Random subspace method for aource camera identification
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Li, Ruizhe, Kotropoulos, C., Li, Chang-Tsun and Guan, Yu (2015) Random subspace method for aource camera identification. In: IEEE International Workshop on Machine Learning for Signal Processing (MLSP'15), Boston, USA, 17-20 Sept 2015. Published in: 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)
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WRAP_Random Subspace Method for Source Camera Identification.pdf - Accepted Version - Requires a PDF viewer. Download (642Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/MLSP.2015.7324339
Abstract
Sensor pattern noise is an inherent fingerprint of imaging devices, which has been widely used for source camera identification, image classification, and forgery detection. In a previous work, we proposed a feature extraction method based on the principal component analysis denoising concept, which can enhance the performance of conventional SPN extraction methods. However, this method is vulnerable, because the training samples are seriously affected by the image content. Accordingly, it is difficult to train a reliable feature extractor by using such a training set. To address this problem, a camera identification framework based on the random subspace method and majority voting is proposed in this work. The experimental results show that the proposed solution can suppress the interference from scene details and enhance the performance in terms of the receiver operating characteristic curve.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Digital cameras -- Identification, Image processing -- Digital techniques, Computer crimes -- Investigation, Pattern recognition systems | ||||||
| Journal or Publication Title: | 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP) | ||||||
| Publisher: | IEEE | ||||||
| Official Date: | 12 July 2015 | ||||||
| Dates: |
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| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Date of first compliant deposit: | 11 January 2016 | ||||||
| Date of first compliant Open Access: | 11 January 2016 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | IEEE International Workshop on Machine Learning for Signal Processing (MLSP'15) | ||||||
| Type of Event: | Workshop | ||||||
| Location of Event: | Boston, USA | ||||||
| Date(s) of Event: | 17-20 Sept 2015 |
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