Resilient Digital Image Watermarking Using a DCT- Component Perturbation Model

The applications of the Discrete Cosine Transform (DCT) for Computer Generated Imagery, image processingand, in particular, image compression are well known and the DCT also forms the central kernel for a number ofdigital image watermarking methods. In this paper we consider the application of the DCT for producing a highlyrobust method of watermarking images using a block partitioning approach subject to a self-alignment strategyand bit error correction. The applications for the algorithms presented include the copyright protection of imagesand Digital Right Management for image libraries, for example. However, the principal focus of the researchreported in this paper is on the use of print-scan and e-display-scan image authentication for use in e-ticketswhere QR code, for example, are embedded in an full colour image of the ticket holder. This requires that a DCTembedding procedure is developed that is highly robust to blur, noise, geometric distortions such as rotation, shift and barrel and the partial removal of image segments, all of which are consider ed in regard to the resilience of the method proposed and its practical realisation in a real operating environment

Resilient Digital Image Watermarking for Document Authentication

Abstract—We consider the applications of the Discrete Cosine Transform (DCT) and then a Chirp coding method for producing a highly robust system for watermarking images using a block partitioning approach subject to a self-alignment strategy and bit error correction. The applications for the algorithms presented and the system developed include the copyright protection of images and Digital Right Management for image libraries, for example. However, the principal focus of the research reported in this paper is on the use of printscan and e-display-scan image authentication for use in e-tickets where QR code, for example, are embedded in a full colour image of the ticket holder. This requires that an embedding procedure is developed that is highly robust to blur, noise, geometric distortions such as rotation, shift and barrel and the partial removal of image segments, all of which are considered in regard to the resilience of the method proposed and its practical realisation in a real operating environment

Statistical Tools for Digital Image Forensics

A digitally altered image, often leaving no visual clues of having been tampered with, can be indistinguishable from an authentic image. The tampering, however, may disturb some underlying statistical properties of the image. Under this assumption, we propose five techniques that quantify and detect statistical perturbations found in different forms of tampered images: (1) re-sampled images (e.g., scaled or rotated); (2) manipulated color filter array interpolated images; (3) double JPEG compressed images; (4) images with duplicated regions; and (5) images with inconsistent noise patterns. These techniques work in the absence of any embedded watermarks or signatures. For each technique we develop the theoretical foundation, show its effectiveness on credible forgeries, and analyze its sensitivity and robustness to simple counter-attacks

Currency security and forensics: a survey

By its definition, the word currency refers to an agreed medium for exchange, a nation’s currency is the formal medium enforced by the elected governing entity. Throughout history, issuers have faced one common threat: counterfeiting. Despite technological advancements, overcoming counterfeit production remains a distant future. Scientific determination of authenticity requires a deep understanding of the raw materials and manufacturing processes involved. This survey serves as a synthesis of the current literature to understand the technology and the mechanics involved in currency manufacture and security, whilst identifying gaps in the current literature. Ultimately, a robust currency is desire

Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

The quality of modern astronomical data, the power of modern computers and the agility of current image-processing software enable the creation of high-quality images in a purely digital form. The combination of these technological advancements has created a new ability to make color astronomical images. And in many ways it has led to a new philosophy towards how to create them. A practical guide is presented on how to generate astronomical images from research data with powerful image-processing programs. These programs use a layering metaphor that allows for an unlimited number of astronomical datasets to be combined in any desired color scheme, creating an immense parameter space to be explored using an iterative approach. Several examples of image creation are presented. A philosophy is also presented on how to use color and composition to create images that simultaneously highlight scientific detail and are aesthetically appealing. This philosophy is necessary because most datasets do not correspond to the wavelength range of sensitivity of the human eye. The use of visual grammar, defined as the elements which affect the interpretation of an image, can maximize the richness and detail in an image while maintaining scientific accuracy. By properly using visual grammar, one can imply qualities that a two-dimensional image intrinsically cannot show, such as depth, motion and energy. In addition, composition can be used to engage viewers and keep them interested for a longer period of time. The use of these techniques can result in a striking image that will effectively convey the science within the image, to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A

Connected Attribute Filtering Based on Contour Smoothness

A new attribute measuring the contour smoothness of 2-D objects is presented in the context of morphological attribute filtering. The attribute is based on the ratio of the circularity and non-compactness, and has a maximum of 1 for a perfect circle. It decreases as the object boundary becomes irregular. Computation on hierarchical image representation structures relies on five auxiliary data members and is rapid. Contour smoothness is a suitable descriptor for detecting and discriminating man-made structures from other image features. An example is demonstrated on a very-high-resolution satellite image using connected pattern spectra and the switchboard platform