Content-based image retrieval is an important area of research. Here, a method to characterize visual appearance for determining global similarity in images is described. Images are filtered with Gaussian derivatives and geometric features are computed from the filtered images. The geometric features used here are curvature and phase. Two images may be said to be similar if they have similar distributions of such features. Global similarity may, therefore, be deduced by comparing histograms of these features. This allows for rapid retrieval. The system's performance on a database of about 1500 grey-level images and another database of 2000 trademark images is shown. It is also shown that the approach is scalable and examples of query results on a database of more than 63000 trademark images are provided.

Funding opportunities and digitisation initiatives offer libraries, galleries and museums the potential to exploit their image collections – photographs, slides, drawings, pictures and works of art – in new and exciting ways. Many different organisations are involved in developing standards for the formal description of images (e.g. artist, title, photographer) and some effort is being made to develop compatible standards for the digital environment. Indexing of images can be a difficult task because images are rich in information and may be used by widely different groups of users, who may not always express their information needs adequately. Content-Based Image Retrieval (CBIR) technology, which allows the retrieval of images based on similarity to a query image, has enormous potential, particularly if it can be combined with text-based indexing.

ABSTRACTAgents of opportunity (AO) in academic medical centers (AMC) are defined as unregulated or lightly regulated substances used for medical research or patient care that can be used as “dual purpose” substances by terrorists to inflict damage upon populations. Most of these agents are used routinely throughout AMC either during research or for general clinical practice. To date, the lack of careful regulations for AOs creates uncertain security conditions and increased malicious potential. Using a consensus-based approach, we collected information and opinions from staff working in an AMC and 4 AMC-affiliated hospitals concerning identification of AO, AO attributes, and AMC risk and preparedness, focusing on AO security and dissemination mechanisms and likely hospital response. The goal was to develop a risk profile and framework for AO in the institution. Agents of opportunity in 4 classes were identified and an AO profile was developed, comprising 16 attributes denoting information critical to preparedness for AO misuse. Agents of opportunity found in AMC present a unique and vital gap in public health preparedness. Findings of this project may provide a foundation for a discussion and consensus efforts to determine a nationally accepted risk profile framework for AO. This foundation may further lead to the implementation of appropriate regulatory policies to improve public health preparedness. Agents of opportunity modeling of dissemination properties should be developed to better predict AO risk.(Disaster Med Public Health Preparedness. 2010;4:318-325)

This paper describes the evaluation of ARTISAN, a system designed to provide automatic retrieval of abstract trademark images by shape feature. The system depends for its operation on analyzing each image to characterize key shape components, grouping image regions into families which potentially mirror human image perception, and then deriving characteristic indexing features from these families. A variety of run-time search options is provided, allowing the user to select alternative sets of shape features and similarity matching paradigms.The system's retrieval effectiveness has been evaluated by measuring its retrieval effectiveness using a set of 12 real queries with known results put to a collection of over 10 000 abstract geometric shapes from the UK Trade Marks Registry. Normalized recall and precision scores averaged 0.93 and 0.65 respectively. The results suggest strongly that the basic ARTISAN approach is valid, though the present version has significant limitations, particularly when handling badly-scanned images or images with implied shape features. Possible ways of overcoming these limitations are discussed.

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As the number of digital images available to art historians grows apace, it is perhaps an opportune moment to consider what impact digital images have had on the discipline and on the work methods of art historians. This paper revisits the findings of a research project – Compare and contrast – focusing on the attitudes of art historians towards digital image technologies, the role of the technologies in the different phases and activities of the research process, the tools and their potential, and barriers to the use of digital images.

A survey undertaken between January and March 1998 investigated the use of information and communication technologies (ICT) in a sample of 120 industrial and commercial libraries. Ninety-six per cent of the organisations which responded to the questionnaire use computers for some aspect of their library and information services. ICT was used for a range of office and other applications including, in rank order, e-mail, word processing, spreadsheets, presentation packages and database management systems. Ninety-one per cent of the sample used various Internet facilities including e-mail, World Wide Web, file transfer protocol (ftp) and telnet. This paper describes the results of the survey, reporting on the current state of the art of ICT use and future plans for automation in the sample.

Before a trade mark can be registered at the UK Patent Office, registrars need to ensure it isn't confusingly similar to any of 300,000 existing marks in the Registry's database. Many trade marks take the form of abstract geometric designs that are especially difficult for indexers and searchers to describe. ARTISAN, developed at the University of Northumbria, is a system that allows such marks to be indexed and retrieved automatically, on the basis of their shape. Evaluative studies have demonstrated the feasibility of this approach, and the newly‐established Institute for Image Data Research plans further development.