Image Hashing Robust Against Cropping and Rotation

Authors

  • Martin Steinebach Fraunhofer SIT/ATHENE, Germany https://orcid.org/0000-0002-0240-0388
  • Tiberius Berwanger TU Darmstadt/ATHENE, Germany
  • Huajian Liu Fraunhofer SIT/ATHENE, Germany

DOI:

https://doi.org/10.13052/jcsm2245-1439.1221

Keywords:

Image identification, robust hashing, feature-based hashing, rotation, segmentation

Abstract

Image recognition is an important mechanism used in various scenarios. In the context of multimedia forensics, its most significant task is to automatically detect already known child and adolescent pornography in a large set of images. When fighting disinformation, it is used to identify images taken out of context or image montages. For this purpose, numerous methods based on robust hashing and feature extraction are already known, and recently also supported by machine learning. However, in general, these methods are either only partially robust to changes such as rotation and pruning, or they require a large amount of data and computation. We present a method based on a simple block hash that is efficient to compute and memory efficient. To be robust against cropping and rotation, we combine the method with image segmentation and a method to normalize the rotation of the objects. Our evaluation shows that the method produces results comparable to much more complex approaches, but requires fewer resources.

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Author Biographies

Martin Steinebach, Fraunhofer SIT/ATHENE, Germany

Martin Steinebach is the manager of the Media Security and IT Forensics division at Fraunhofer SIT. From 2003 to 2007 he was the manager of the Media Security in IT division at Fraunhofer IPSI. He studied computer science at the Technical University of Darmstadt and finished his diploma thesis on copyright protection for digital audio in 1999. In 2003 he received his PhD at the Technical University of Darmstadt for this work on digital audio watermarking. In 2016 he became honorary professor at the TU Darmstadt. He gives lectures on Multimedia Security as well as Civil Security. He is Principle Investigator at ATHENE and represents IT Forensics and AI security. Before he was Principle Investigator at CASED with the topics Multimedia Security and IT Forensics. In 2012 his work on robust image hashing for detection of child pornography reached the second rank “Deutscher ITSicherheitspreis”, an award funded by Host Görtz.

Huajian Liu, Fraunhofer SIT/ATHENE, Germany

Huajian Liu received his B.S. and M.S. degrees in electronic engineering from Dalian University of Technology, China, in 1999 and 2002, respectively, and his Ph.D. degree in computer science from Technical University Darmstadt, Germany, in 2008. He is currently a senior research scientist at Fraunhofer Institute for Secure Information Technology (SIT). His major research interests include information security, digital watermarking, robust hashing and digital forensics.

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Published

2023-05-03

How to Cite

1.
Steinebach M, Berwanger T, Liu H. Image Hashing Robust Against Cropping and Rotation. JCSANDM [Internet]. 2023 May 3 [cited 2024 Nov. 2];12(02):129-60. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/19049

Issue

2023: Vol 12 Iss 2

Section

ARES 2022 Workshops

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