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Copy-Move Forgery Detection and Localization via Partial Audio Matching

 
: Maksimovic, Milica; Cuccovillo, Luca; Aichroth, Patrick

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Volltext ()

AES E-Library. Online resource (2019), Paper Nr.24
http://www.aes.org/e-lib/
International Conference on Audio Forensics <2019, Porto>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IDMT ()

Abstract
In this paper, we present a new approach for detecting and localizing copy-move forgeries within digital audio recordings. The approach is based on an audio fingerprinting and matching algorithm that was originally designed for partial audio matching without a query for large datasets, which was now successfully adapted to the speci?c requirements of copy-move forgery detection, i.e. short segment duration and high reliability. Thanks to the characteristics of the original algorithm, our proposed approach does not require pre-segmentation, and shows high accuracy for detection and localization of copy move forgery, including mismatching background noise, thereby significantly extending the state-of-the art.

: http://publica.fraunhofer.de/dokumente/N-564754.html