Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7427
Title: Seam-Carving Based Anonymization Against Image & Video Source Attribution
Authors: Bayram, Sevinç
Sencar, Hüsrev Taha
Memon, Nasir
Keywords: [No Keywords]
Publisher: IEEE
Source: 15th IEEE International Workshop on Multimedia Signal Processing (MMSP) -- SEP 30-OCT 02, 2013 -- ITALY
Series/Report no.: IEEE International Workshop on Multimedia Signal Processing
Abstract: As image source attribution techniques have become significantly sophisticated and are now becoming commonplace, there is a growing need for capabilities to anonymize images and videos. Focusing on the photo response non-uniformity noise pattern based sensor fingerprinting technique, this work evaluates the effectiveness of well-established seam carving method to defend against sensor fingerprint matching. We consider ways in which seam-carving based anonymization can be countered and propose enhancements over conventional seam carving method. Our results show that applying geometrical distortion in addition to seam carving will make counter attack very ineffective both in terms of computational complexity and accuracy.
URI: https://hdl.handle.net/20.500.11851/7427
ISBN: 978-1-4799-0125-8
ISSN: 2163-3517
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

WEB OF SCIENCETM
Citations

17
checked on Dec 21, 2024

Page view(s)

56
checked on Dec 16, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.