TR2010-005

Hiding Information Inside Structured Shapes


    •  Das, S., Rane, S.D., Vetro, A., "Hiding Information Inside Structured Shapes", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2010.
      BibTeX TR2010-005 PDF
      • @inproceedings{Das2010mar,
      • author = {Das, S. and Rane, S.D. and Vetro, A.},
      • title = {Hiding Information Inside Structured Shapes},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2010,
      • month = mar,
      • url = {https://www.merl.com/publications/TR2010-005}
      • }
  • MERL Contact:
  • Research Area:

    Information Security

Abstract:

This paper describes a new technique for embedding a message within structured shapes. It is desired that my changes in the shape owing to the embedded message are invisible to a casual observer but detectable by a specialized decoder. The message embedding algorithm represents shape outline as a set of cubic Bezier curves and straight line segments. By slightly perturbing the Bezier curves, a single shape can spawn a library of similar-looking shapes each corresponding to a unique message. This library is efficiently stored using Adaptively Sampled Distance Fields (ADFs) which also facilitate rendering of the modified shapes at the desired resolution and fidelity. Given any modified shape, a forensic detector applies Procrustes analysis to determine the embedded message. Results of an extensive subjective test confirm that the shape modifications are indeed unobtrusive. Further, to test the recovery of the message bits in noisy physical environments, a text document is put through a print-photocopy-scan process. Message recovery is found to be stable even after multiple rounds of photocopying.

 

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      Date: March 14, 2010
      Where: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
      MERL Contacts: Anthony Vetro; Petros T. Boufounos
      Brief
      • The papers "Privacy and Security of Features Extracted from Minutiae Aggregates" by Nagar, A., Rane, S.D. and Vetro, A., "Hiding Information Inside Structured Shapes" by Das, S., Rane, S.D. and Vetro, A., "Ultrasonic Sensing for Robust Speech Recognition" by Srinivasan, S., Raj, B. and Ezzat, T., "Reconstruction of Sparse Signals from Distorted Randomized Measurements" by Boufounos, P.T., "Disparity Search Range Estimation: Enforcing Temporal Consistency" by Min, D., Yea, S., Arican, Z. and Vetro, A., "Synthesizing Speech from Doppler Signals" by Toth, A.R., Raj, B., Kalgaonkar, K. and Ezzat, T., "Spectrogram Dimensionality Reduction with Independence Constraints" by Wilson, K.W. and Raj, B., "Robust Regression using Sparse Learning for High Dimensional Parameter Estimation Problems" by Mitra, K., Veeraraghavan, A.N. and Chellappa, R. and "Subword Unit Approaches for Retrieval by Voice" by Gouvea, E., Ezzat, T. and Raj, B. were presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
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