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J. Imaging 2018, 4(4), 56; https://doi.org/10.3390/jimaging4040056

Detection of Orientation-Modulation Embedded Data in Color Printed Natural Images

Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjovik, Norway
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Received: 10 March 2018 / Revised: 27 March 2018 / Accepted: 29 March 2018 / Published: 4 April 2018
(This article belongs to the Special Issue Computational Colour Imaging)
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Abstract

This article addresses methods for detection of orientation-modulation data embedded in color dispersed-dot-halftone images. Several state-of-the-art methods for detection of orientation-embedded data in printed halftone images have been proposed, however they have only been evaluated independently without comparing with each other. We propose an improved detection method, which is using Principal Component Analysis (PCA) components as oriented-feature extractors, and a probabilistic model for the print-and-scan channel for maximum likelihood detection. The proposed detector and four state-of-the-art detectors are compared with each other in terms of correct detection rate, using a comprehensive testing set of printed natural images captured with three different devices. The proposed detector achieves highest correct detection rate using fewer feature extractors than the other methods, and it is significantly more robust to non-calibrated devices used for capturing the printed images. This is mostly due to the improved PCA-based oriented-feature extractors that are responsive to the embedded orientations and robust and insensitive to the other visual content. View Full-Text
Keywords: halftoning; watermarking; watermark detection; orientation modulation; data hiding; data embedding; dispersed-dot; direct binary search halftoning; watermarking; watermark detection; orientation modulation; data hiding; data embedding; dispersed-dot; direct binary search
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kitanovski, V.; Pedersen, M. Detection of Orientation-Modulation Embedded Data in Color Printed Natural Images. J. Imaging 2018, 4, 56.

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