Incremental update of feature extractor for camera identification
conference contribution
posted on 2015-01-01, 00:00 authored by R Li, Chang-Tsun LiChang-Tsun Li, Y Guan© 2015 IEEE. Sensor Pattern Noise (SPN) is an inherent fingerprint of imaging devices, which has been widely used in the tasks of digital camera identification, image classification and forgery detection. In our previous work, a feature extraction method based on PCA denoising concept was applied to extract a set of principal components from the original noise residual. However, this algorithm is inefficient when query cameras are continuously received. To solve this problem, we propose an extension based on Candid Covariance-free Incremental PCA (CCIPCA) and two modifications to incrementally update the feature extractor according to the received cameras. Experimental results show that the PCA and CCIPCA based features both outperform their original features on the ROC performance, and CCIPCA is more efficient on camera updating.
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Pagination
324-328Location
Quebec City, CanadaPublisher DOI
Start date
2015-09-27End date
2015-09-30ISSN
1522-4880ISBN-13
9781479983391Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2015, IEEETitle of proceedings
ICIP 2015 : Proceedings of the IEEE International Conference on Image ProcessingEvent
Image Processing. International Conference (2015 : Quebec City, Canada)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
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