NDLI: Unsupervised classification of digital images using enhanced sensor pattern noise

Content Provider	IEEE Xplore Digital Library
Author	Chang-Tsun Li
Copyright Year	2010
Description	Author affiliation: Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK (Chang-Tsun Li)
Abstract	We present in this work an unsupervised image classifier, which is capable of clustering images taken by an unknown number of unknown digital cameras into a number of classes, each corresponding to one camera. The classification system first extracts and enhances a sensor pattern noise (SPN) from each image, which serves as the fingerprint of the camera that has taken the image. Secondly, it applies an unsupervised classifier trainer to a small training set of randomly selected SPNs to cluster the SPNs into classes and uses the centroids of those identified classes as the trained classifier. The classifier trainer treats each SPN as a random variable and uses Markov random field (MRF) approach to iteratively assigns a class label to each SPN (i.e., random variable) based on the class labels assigned to the members of a small set of SPNs, called membership committee, and the similarity values between it and the members of the membership committee until a stop criteria is met. The classifier trainer requires no a priori knowledge about the dataset from the user. Finally the image not included in the small training set are classified using the trained classifier depending on the similarity between their SPNs and the centroids of the trained classifier.
Starting Page	3429
Ending Page	3432
File Size	269163
Page Count	4
File Format	PDF
ISBN	9781424453085
DOI	10.1109/ISCAS.2010.5537850
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-30
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Digital images Image sensors Fingerprint recognition Digital cameras Membership Committee Random variables Forensics Image analysis Digital filters Computer science sensor pattern noise Image classification machine learning digital forensics
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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