Share Email Print
cover

Proceedings Paper

Data embedding in hardcopy images via halftone-dot orientation modulation
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The principal challenge in hardcopy data hiding is achieving robustness to the print-scan process. Conventional robust hiding schemes are not well-suited because they do not adapt to the print-scan distortion channel, and hence are fundamentally limited in a detection theoretic sense. We consider data embedding in images printed with clustered dot halftones. The input to the print-scan channel in this scenario is a binary halftone image, and hence the distortions are also intimately tied to the nature of the halftoning algorithm employed. We propose a new framework for hardcopy data hiding based on halftone dot orientation modulation. We develop analytic halftone threshold functions that generate elliptically shaped halftone dots in any desired orientation. Our hiding strategy then embeds a binary symbol as a particular choice of the orientation. The orientation is identified at the decoder via statistically motivated moments following appropriate global and local synchronization to adress the geometric distortion introduced by the print scan channel. A probabilistic model of the print-scan process, which conditions received moments on input orientation, allows for Maximum Likelihood (ML) optimal decoding. Our method bears similarities to the paradigms of informed coding and QIM, but also makes departures from classical results in that constant and smooth image areas are better suited for embedding via our scheme as opposed to busy or "high entropy" regions. Data extraction is automatically done from a scanned hardcopy, and results indicate significantly higher embedding rate than existing methods, a majority of which rely on visual or manual detection.

Paper Details

Date Published: 18 March 2008
PDF: 12 pages
Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190C (18 March 2008); doi: 10.1117/12.767408
Show Author Affiliations
Orhan Bulan, Univ. of Rochester (United States)
Vishal Monga, Xerox Corp. (United States)
Gaurav Sharma, Univ. of Rochester (United States)
Basak Oztan, Univ. of Rochester (United States)


Published in SPIE Proceedings Vol. 6819:
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
Edward J. Delp; Ping Wah Wong; Jana Dittmann; Nasir D. Memon, Editor(s)

© SPIE. Terms of Use
Back to Top