Printer and Scanner Forensics

Ho, Anthony T. S.; Li, Shujun

doi:10.1002/9781118705773.ch10

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…However, they typically suffer from generalization issues due to the high variability of pre- and postprocessing operations which should be expected in real world scenarios [ 7 ]. In fact, as widely investigated in the field of image forensics, steps like compression [ 8 ], printing/scanning operations [ 9 ], resizing [ 10 ], and aspect ratio correction might be applied to the photo under investigation with highly diverse parameters and in turn introduce further subtle distortions and artifacts, which can have a strong impact on the (typically weak) morphing traces in the image signal [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Detecting Morphing Attacks through Face Geometry Features

Autherith

Pasquini

2020

J. Imaging

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Face-morphing operations allow for the generation of digital faces that simultaneously carry the characteristics of two different subjects. It has been demonstrated that morphed faces strongly challenge face-verification systems, as they typically match two different identities. This poses serious security issues in machine-assisted border control applications and calls for techniques to automatically detect whether morphing operations have been previously applied on passport photos. While many proposed approaches analyze the suspect passport photo only, our work operates in a differential scenario, i.e., when the passport photo is analyzed in conjunction with the probe image of the subject acquired at border control to verify that they correspond to the same identity. To this purpose, in this study, we analyze the locations of biologically meaningful facial landmarks identified in the two images, with the goal of capturing inconsistencies in the facial geometry introduced by the morphing process. We report the results of extensive experiments performed on images of various sources and under different experimental settings showing that landmark locations detected through automated algorithms contain discriminative information for identifying pairs with morphed passport photos. Sensitivity of supervised classifiers to different compositions on the training and testing sets are also explored, together with the performance of different derived feature transformations.

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Section: Introductionmentioning

confidence: 99%

Detecting Morphing Attacks through Face Geometry Features

Autherith

Pasquini

2020

J. Imaging

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“…It is then digitized through the ADC, and postprocessing is performed to adjust contrast and enhance visibility. The final digital image is obtained after file compression [16,21,22].…”

mentioning

confidence: 99%