Benedikt Lorch, M. Sc.
- Organization: Department of Computer Science
- Working group: Chair of Computer Science 1 (IT Security Infrastructures)
- Phone number: +49 9131 85 69918
- Fax number: +49 9131 85 69919
- Email: email@example.com
- Website: https://www.cs1.tf.fau.de/
- Address: Martensstr. 3
91058 ErlangenRoom 12.139
PhD candidate in the multimedia security group. My research interests include image forensics, computer vision, and machine learning.
Image forensics from chroma wrinkles
The JPEG compression format provides a rich source of forensic traces that include quantization artifacts, fingerprints of the container format, and numerical particularities of JPEG compressors. Such a diverse set of cues serves as the basis for a forensic examiner to determine origin and authenticity of an image. In this work, we present a novel artifact that can be used to fingerprint the JPEG compression library. The artifact arises from chroma subsampling in one of the most popular JPEG implementations. Due to integer rounding, every second column of the compressed chroma channel appears on average slightly brighter than its neighboring columns, which is why we call the artifact a chroma wrinkle. We theoretically derive the chroma wrinkle footprint in DCT domain, and use this footprint for detecting chroma wrinkles.
Paper | Slides
Forensic reconstruction of severely degraded license plates
Forensic investigations often have to contend with extremely low-quality images that can provide critical evidence. Recent work has shown that, although not visually apparent, information can be recovered from such low-resolution and degraded images. We developed a CNN-based approach to decipher the contents of low-quality images of license plates.
Paper | Slides | GitHub
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- Lorch, B., Agarwal, S., & Farid, H. (2019). Forensic Reconstruction of Severely Degraded License Plates. In Society for Imaging Science & Technology (Eds.), Electronic Imaging. Burlingame, CA, US.
- Lorch, B., & Riess, C. (2019). Image Forensics from Chroma Subsampling of High-Quality JPEG Images. In Proceedings of the ACM Workshop on Information Hiding and Multimedia Security. Paris, FR.
- Lorch, B., Vaillant, G., Baumgartner, C., Bai, W., Rueckert, D., & Maier, A. (2017). Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests. Journal of Medical Engineering, 2017. https://dx.doi.org/10.1155/2017/4501647
- Lorch, B., Berger, M., Hornegger, J., & Maier, A. (2015). Projection and Reconstruction-Based Noise Filtering Methods in Cone Beam CT. In Bildverarbeitung für die Medizin 2015 (pp. 59-64). Lübeck.
- Mullan, P., Kanzler, C., Lorch, B., Schroeder, L., Winkler, L., Larissa, L.,... Pasluosta, C.F. (2015). Unobtrusive Heart Rate Estimation during Physical Exercise using Photoplethysmographic and Acceleration Data. In 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC ’15. Milano.