Reading between the pixels: Photographic steganography for camera display messaging

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

8 Scopus citations

Abstract

We exploit human color metamers to send light-modulated messages decipherable by cameras, but camouflaged to human vision. These time-varying messages are concealed in ordinary images and videos. Unlike previous methods which rely on visually obtrusive intensity modulation, embedding with color reduces visible artifacts. The mismatch in human and camera spectral sensitivity creates a unique opportunity for hidden messaging. Each color pixel in an electronic display image is modified by shifting the base color along a particular color gradient. The challenge is to find the set of color gradients that maximizes camera response and minimizes human response. Our approach does not require a priori measurement of these sensitivity curves. We learn an ellipsoidal partitioning of the 6-dimensional space of base colors and color gradients. This partitioning creates metamer sets defined by the base color of each display pixel and the corresponding color gradient for message encoding. We sample from the learned metamer sets to find optimal color steps for arbitrary base colors. Ordinary displays and cameras are used, so there is no need for high speed cameras or displays. Our primary contribution is a method to map pixels in an arbitrary image to metamer pairs for steganographic camera-display messaging.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Computational Photography, ICCP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509057450
DOIs
StatePublished - Jun 16 2017
Event2017 IEEE International Conference on Computational Photography, ICCP 2017 - Stanford, United States
Duration: May 12 2017May 14 2017

Publication series

Name2017 IEEE International Conference on Computational Photography, ICCP 2017 - Proceedings

Other

Other2017 IEEE International Conference on Computational Photography, ICCP 2017
CountryUnited States
CityStanford
Period5/12/175/14/17

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

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