| Title | Generalized Benford's Law for Blind Detection of Morphed Face Images |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Makrushin, Andrey, Kraetzer, Christian, Neubert, Tom, Dittmann, Jana |
| Conference Name | Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5625-1 |
| Keywords | digital image forensics, face morphing, Human Behavior, information forensics, Metrics, morphing detection, pubcrawl, resilience, Scalability |
| Abstract | A morphed face image in a photo ID is a serious threat to image-based user verification enabling that multiple persons could be matched with the same document. The application of machine-readable travel documents (MRTD) at automated border control (ABC) gates is an example of a verification scenario that is very sensitive to this kind of fraud. Detection of morphed face images prior to face matching is, therefore, indispensable for effective border security. We introduce the face morphing detection approach based on fitting a logarithmic curve to nine Benford features extracted from quantized DCT coefficients of JPEG compressed original and morphed face images. We separately study the parameters of the logarithmic curve in face and background regions to establish the traces imposed by the morphing process. The evaluation results show that a single parameter of the logarithmic curve may be sufficient to clearly separate morphed and original images. |
| URL | http://doi.acm.org/10.1145/3206004.3206018 |
| DOI | 10.1145/3206004.3206018 |
| Citation Key | makrushin_generalized_2018 |
Generalized Benford's Law for Blind Detection of Morphed Face Images