Issues on Selecting Image Features for Robust Source Camera Identification

Yongjian Hu, Chang-Tsun Li, Changhui Zhou, Xufeng Lin

Research output: Book chapter/Published conference paperConference paperpeer-review


Image feature selection is an important issue for source camera identification. Well-selected features should make camera classifiers accurate, efficient as well as robust. Current source camera identification schemes select image features mainly based on classification accuracy and computational efficiency. In this work, we demonstrate that robustness should also be considered for classifiers which aim at real-world tasks. Besides, we reveal what impact the reduced feature subset will have on the robustness of camera classifiers. The dimensionality reduction is often necessary for computational efficiency.
Original languageEnglish
Title of host publicationProceedings of the Sixth International Workshop on Digital Forensics and Incident Analysis
Subtitle of host publicationWDFIA 2011
Place of PublicationUK
PublisherUniversity of Plymouth
Number of pages10
Publication statusPublished - 2011
Event6th Annual Workshop on Digital Forensics & Incident Analysis: WDFIA 2011 - Kingston University, London, United Kingdom
Duration: 07 Jul 201108 Jul 2011


Conference6th Annual Workshop on Digital Forensics & Incident Analysis
CountryUnited Kingdom
Internet address

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