Hiding information inside structured shapes

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. IEEE International Conference on Acoustics, Speech and Signal ProcessingThis work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. ABSTRACT This paper describes a new technique for embedding a message within structured shapes. It is desired that any 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 outlines 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.

Multi-level QR code with Hill Climbed Encrypted Public Level for Secured Message Transfer

“…Wu and Liu [1] thought of a plan to utilize parallel pictures and inserting the information in ti dependent on the square based relationship However the picture twists is gigantic in this impact along these lines to beat this downside Yang and Kot [2] proposed the idea of visually impaired information with huge capacity limit and decent visual morals quality anyway this could be appropriate just to the paired components Varna et al [3] proposed another methodology for drubbing information into the content reports with changing long arrangements of characters however this idea can be just relevant to the characters not ASCII esteems. Das et al [4] thought of the thought by changing the other bend parameters in non-straight portions with the predefined shapes also.…”

“…Because of the above reason, the dark modules are not being changed.The public message(Mpub) that needs to be encrypted will undergo the encryption techniques while key that will be encrypted will also be sent via the QR code. The encryption technique [4] to be utilized here to encode the open key is the all-encompassing slope figure calculation where in which the accompanying advances will be tolerated to make the information scrambled. At first the open information which should be scrambled is taken and there is no imperative on the information both the tally and the information will be masterminded in the request of the square lattice where in which the request is being chosen by the framework and should likewise be possible by the client.…”

Particle filtering on large dimensional state spaces and applications in computer vision

“…We have also successfully demonstrated the use of the NSSA for modelbased compression of landmark shape sequence data. In addition, the landmark shape based techniques discussed in this chapter has been extended to steganographic applications for hiding binary information inside structured shapes like text characters and glyphs 2 (more details in [83,84]. A patent has been filed : US Patent No.…”