John Stach

A high-capacity invertible data-hiding algorithm using a generalized reversible integer transform

A high-capacity, data-hiding algorithm that lets the user restore the original host image after retrieving the hidden data is presented in this paper. The proposed algorithm can be used for watermarking valuable or sensitive images such as original art works or military and medical images. The proposed algorithm is based on a generalized, reversible, integer transform, which calculates the average and pair-wise differences between the elements of a vector extracted from the pixels of the image. The watermark is embedded into a set of carefully selected coefficients by replacing the least significant bit (LSB) of every selected coefficient by a watermark bit. Most of these coefficients are shifted left by one bit before replacing their LSBs. Several conditions are derived and used in selecting the appropriate coefficients to ensure that they remain identifiable after embedding. In addition, the selection of coefficients ensures that the embedding process does not cause any overflow or underflow when the inverse of the transform is computed. To ensure reversibility, the locations of the shifted coefficients and the original LSBs are embedded in the selected coefficients before embedding the desired payload. Simulation results of the algorithm and its performance are also presented and discussed in the paper.

Real-time application of digital watermarking to embed tactical metadata into full motion video captured from unmanned aerial systems

A persistent challenge with imagery captured from Unmanned Aerial Systems (UAS), is the loss of critical information such as associated sensor and geospatial data, and prioritized routing information (i.e., metadata) required to use the imagery effectively. Often, there is a loss of synchronization between data and imagery. The losses usually arise due to the use of separate channels for metadata, or due to multiple imagery formats employed in the processing and distribution workflows that do not preserve the data. To contend with these issues and provide another layer of authentication, digital watermarks were inserted at point of capture within a tactical UAS. Implementation challenges included traditional requirements surrounding, image fidelity, performance, payload size, robustness and application requirements such as power consumption, digital to analog conversion and a fixed bandwidth downlink, as well as a standard-based approach to geospatial exploitation through a serviceoriented- architecture (SOA) for extracting and mapping mission critical metadata from the video stream. The authors capture the application requirements, implementation trade-offs and ultimately analysis of selected algorithms. A brief summary of results is provided from multiple test flights onboard the SkySeer test UAS in support of Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance applications within Network Centric Warfare and Future Combat Systems doctrine.

New wrinkle in dirty paper techniques

The many recent publications that focus upon watermarking with side information at the embedder emphasize the fact that this side information can be used to improve practical capacity. Many of the proposed algorithms use quantization to carry out the embedding process. Although both powerful and simple, recovering the original quantization levels, and hence the embedded data, can be difficult if the image amplitude is modified. In our paper, we present a method that is similar to the existing class of quantization-based techniques, but is different in the sense that we first apply a projection to the image data that is invariant to a class of amplitude modifications that can be described as order preserving. Watermark reading and embedding is done with respect to the projected data rather than the original. Not surprisingly, by requiring invariance to amplitude modifications we increase our vulnerability to other types of distortions. Uniform quantization of the projected data generally leads to non-uniform quantization of the original data, which in turn can cause greater susceptibility to additive noise. Later in the paper we describe a strategy that results in an effective compromise between invariance to amplitude modification and noise susceptibility.

Use of web cameras for watermark detection

Many articles covering novel techniques, theoretical studies, attacks, and analyses have been published recently in the field of digital watermarking. In the interest of expanding commercial markets and applications of watermarking, this paper is part of a series of papers from Digimarc on practical issues associated with commercial watermarking applications. In this paper we address several practical issues associated with the use of web cameras for watermark detection. In addition to the obvious issues of resolution and sensitivity, we explore issues related to the tradeoff between gain and integration time to improve sensitivity, and the effects of fixed pattern noise, time variant noise, and lens and Bayer pattern distortions. Furthermore, the ability to control (or at least determine) camera characteristics including white balance, interpolation, and gain have proven to be critical to successful application of watermark readers based on web cameras. These issues and tradeoffs are examined with respect to typical spatial-domain and transform-domain watermarking approaches.

Machine vision applications of digital watermarking

In the realm of digital watermarks applied to analog media, publications have mostly focused on applications such as document authentication, security, and links where synchronization is merely used to read the payload. In recent papers, we described issues associated with the use of inexpensive cameras to read digital watermarks [5], and we have discussed product development issues associated with the use of watermarks for several applications [3.4.6]. However, the applications presented in these papers also have been focused on the detection and use of the watermark payload as the critical technology. In this paper, we will extend those ideas by examining a wider range of analog media such as objects and surfaces and by examining machine vision applications where the watermark synchronization method (i.e., synchronizing the watermark orientation so that a payload can be extracted) and the design characteristics of the watermark itself are as critical to the application as recovering the watermark payload. Some examples of machine vision applications that could benefit from digital watermarking technology are autonomous navigation, device and robotic control, assembly and parts handling, and inspection and calibration systems for nondestructive testing and analysis. In this paper, we will review some of these applications and show how combining synchronization and payload data can significantly enhance and broaden many machine vision applications.