Towards camera identification from cropped query images

Waheeb Yaqub, Manoranjan Mohanty, Nasir Memon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


PRNU (Photo Response Non-Uniformity)-based camera fingerprints are useful for identifying the source camera of an anonymous image. As the query image has to be correlated with each candidate camera fingerprint, one key concern of this approach is the high run time overhead when using a large camera database. Clever techniques have been proposed to reduce the computation and I/O time either by reducing the size of the fingerprint or by group testing where multiple candidate fingerprints can be eliminated by a single correlation operation. However, these techniques assume that the query images have not been scaled or cropped. In practice this may often not be the case, especially when query images are taken from social media sites. This paper presents a simple scaling-based approach for source camera identification when the query image is of full resolution or if it is cropped from an unknown location (of the original image). The proposed approach can also be easily combined with other known approaches for PRNU matching of scaled images. Experiments using 250 cameras showed that the run time overhead can decrease by a factor 13 when the query is a cropped image.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781479970612
StatePublished - Aug 29 2018
Event25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
Duration: Oct 7 2018Oct 10 2018

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Conference25th IEEE International Conference on Image Processing, ICIP 2018


  • Camera Fingerprint
  • PRNU
  • Source Camera Identification

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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