Content-based image retrieval and its benefits for the stock photography market

The development of powerful low-cost desktop computer systems has changed the pre-press business where tight deadlines must be met per sistently. An increasing number of newspapers and magazines are acquiring, handling, and storing images digitally while the use of hardcopies and slides decreases. Today\u27s computers and high capacity storage-media enable stock pho tography agencies to build digital image databases, giving users fast access to large numbers of images. However, the transition from analog to digital image archives imposes new problems: with thousands of images at hand, the search for a particular image may turn into the search for the needle in a haystack. The first image Database Management Systems (DBMSs) were extended text DBMSs, which stored the image data along with a set of manually entered descriptive keywords. The major problem with this approach is that there is no generally agreed-upon language to describe images. Even sophis ticated DBMSs are unable to detect synonyms; hence, an image described with certain properties such as curvy may not be found if a user enters wavy as a search criterion. Furthermore, some image properties are hard to describe with keywords. A search is likely to fail if properties were not described at the database population stage when images are added to the database. Finally, assigning a sufficient set of keywords to every image adds a tremendous amount of labor to the population stage. Research at many scientific institutions and companies is geared towards overcoming the shortcomings of image DBMSs with keyword-based search engines. Pattern recognition which allows for comparing images based on their visual content is being introduced to image DBMSs, improving the accuracy of search engines. Sketches, sample images, and other means of describing the visual content of images may be used as search criteria in addition to keywords. This thesis project summarizes the basics of pattern recognition and its applications in image database management for contentbased image retrieval. The purpose of this thesis project is to determine the impact of contentbased image retrieval on the stock photography market in the near future. In order to obtain the necessary information, two different questionnaires were sent out to a number of selected stock photography agencies, newspapers, and magazines. The evaluation of the replies was conducted for the three groups separately. The replies from stock photography agencies showed a high interest in digital image archives. They also showed concerns about increased overhead with digital archives. The estimated amount of work required for categoriz ing images and assigning keywords ranged from fifty to ninety percent as compared to ten to fifty percent for scanning. All survey participants agreed that pattern recognition can improve the accuracy of keyword-based search engines. However, they all denied that this approach would reduce the need for assigning keywords. Different needs could be determined for newspaper and magazines. Newspapers rely heavily on keywords since images are often chosen based upon the circumstances under which they were taken while their visual con tent may be secondary. Therefore, newspapers\u27 profits from content-based image retrieval are minute. For magazines, the visual content of images seemed to have a higher priority and the appreciation for corresponding search capabilities was accordingly higher. To summarize, users of digital image archives can profit from contentbased image retrieval if the visual content is an important issue. For image providers, there are a number of reasons that delay the transition to contentbased image retrieval. Currently, there is only one shrink-wrapped commer cial product available that meets the needs of stock photography agencies. This product requires additional work for fully exhausting its capabilities. Finally, many companies have already built their image database and the transition to another system is time-consuming, expensive, and risky

Multimedia applications in production information management.

by Ip Kin-ting, Joma.Thesis (M.B.A.)--Chinese University of Hong Kong, 1993.Includes bibliographical references (leaves 47-49).ABSTRACT --- p.iiTABLE OF CONTENTS --- p.iiiACKNOWLEDGEMENTS --- p.vChapterChapter I. --- INTRODUCTION --- p.1Background --- p.1Objective --- p.2Report Organization --- p.2Chapter II. --- RESEARCH METHODOLOGY --- p.3Methodology --- p.3Problem Definition --- p.3Information Needs --- p.3Information Collection --- p.4Analysis and Conclusion --- p.4Chapter III. --- MULTIMEDIA TECHNOLOGY - AN OVERVIEW --- p.5Definition --- p.5Benefits --- p.6Major Components of Multimedia systems --- p.6Typical Multimedia Systems --- p.12Multimedia Standards --- p.15Existing Multimedia Applications --- p.16The Trend --- p.18Summary --- p.20Chapter IV. --- PRODUCTION MANAGEMENT - AN OVERVIEW --- p.22Definition --- p.22Major Production Management Activities --- p.22Manufacturing Resource Planning --- p.26Just-in-time Manufacturing --- p.27Computerised Production Information Systems --- p.28The Trend --- p.32Summary --- p.34Chapter V. --- INTERVIEW REPORTS --- p.35Rototech --- p.35Kitty & Kettie Supermarket Limited --- p.36Summary --- p.36Chapter VI. --- MULTIMEDIA TECHNOLOGY IN PRODUCTION INFORMATION MANAGEMENT --- p.37The Role of Multimedia Technology in Production Information Management --- p.37Existing Applications --- p.38The Opportunities --- p.41Summary --- p.43Chapter VII. --- CONCLUSIONS AND RECOMMENDATIONS --- p.44BIBLIOGRAPHY --- p.4

COSPO/CENDI Industry Day Conference

The conference's objective was to provide a forum where government information managers and industry information technology experts could have an open exchange and discuss their respective needs and compare them to the available, or soon to be available, solutions. Technical summaries and points of contact are provided for the following sessions: secure products, protocols, and encryption; information providers; electronic document management and publishing; information indexing, discovery, and retrieval (IIDR); automated language translators; IIDR - natural language capabilities; IIDR - advanced technologies; IIDR - distributed heterogeneous and large database support; and communications - speed, bandwidth, and wireless

A guide to computer-based training for the graphic arts industry

Industry in the United States is facing one of the greatest hurdles of all time, that of retraining its work force. The printing industry, in particular, faces a continuing lack of experienced and knowledgeable people. It has begun cooperative efforts to retrain workers in the basic skills needed to run a printing operation. Subjects like basic math, accounting, writing, and sciences round out the curriculum. Also on the scene are entrepreneurial training firms. Off-site training typically goes for $250-350 per person per day; the on-site instruction goes for$400 and up. And then there are options like computer-based tutorials. A firm in San Francisco ships an animated lesson on chokes and spreads to desktop publishers for $20. The demand for this packaging of instructional material has been high. But is it effective

Structured Knowledge Representation for Image Retrieval

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete client-server image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval

Design of a performance evaluation tool for multimedia databases with special reference to Oracle

Increased production and use of multimedia data has led to the development of a more advanced Database Management System (DBMS), like an Object Relational Database Management System (ORDBMS). These advanced databases are necessitated by the complexity in structure and the functionality required by multimedia data. Unfortunately, no suitable benchmarks exist with which to test the performance of databases when handling multimedia data. This thesis describes the design of a benchmark to measure the performance of basic functionality found in multimedia databases. The benchmark, called MORD (Multimedia Object Relational Databases), targets Oracle, a well known commercial Object Relational Database Management System (ORDBMS) that can handle multimedia data. Although MORD targets Oracle, it can easily be applied to other Multimedia Database Management System (MMDBMS) as a result of a design that stressed its portability, and simplicity. MORD consists of a database schema, test data, and code to simulate representative queries on multimedia databases. A number of experiments are described that validate MORD and ensure its correct design and that its objectives are met. A by-product of these experiments is an initial understanding of the performance of multimedia databases. The experiments show that with multimedia data the buffer cache should be at least large enough to hold the largest dataset, a bigger block size improves the performance, and turning off logging and caching for bulk loading improves the performance. MORD can be used to compare different ORDBMS or to assist in the configuration of a specific database

Structured Knowledge Representation for Image Retrieval

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete clientserver image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval

Fundementals of digital imaging

This thesis project shows that conventional photography and digital imaging are two visual media with very distinct differences: A conventional photograph is a human-readable information entity with an actual physical body in the form of silver clusters or color molecules embedded in gelatin. Silver halide materials have a chemical attribute and are organic, almost living organisms affected by heat, moisture, light and pollution, similar as we are. The actual information contained in a photographic image is always overlaid by an unwanted signal called noise. In conventional photography noise becomes visual as graininess. The amount of information in a photographic image cannot be determined exactly and there is always a significant loss of information from image generation to image generation (multiple generation loss). Because objects record themselves on light sensitive silver halide materials using light as a messenger, a photographic image is directly connected to reality, stenciled from the real. This fact is one of the reasons why photography as a medium has a high level of credibility. Despite all the medium inherent subjective, selective and abstractive factors, photography still has the stamp of an objective and reliable source of information, a stamp of authenticity. A digital image is an immaterial, machine-readable stream of bits in the form of a matrix. This numeric structure can be easily altered and manipulated, not only in the space but also in the frequency domain. The solid bond which connects the conventional photographic image to reality disappears with digital imagery. The image is simply itself, has no chemical attribute, and contains no evidence that something existed in reality. The amount of information in a digital image can be exactly determined. However, there is also a certain amount of noise present which, however, cannot be compared with the graininess of photographic materials. Digital information can be compressed with or without a visual loss. Transmission of digital information is easier and more reliable because the information can be error corrected. More than 150 years after the discovery of the photographic process, the wide availability of the tools of digital imaging make it clear to the public that mechanical images are not, and never have been, a reliable source of information. This thesis project points out that the belief in the objectivity of photographic information was, and is, an illusion. The thesis project Fundamentals of Digital Imaging analyzes the basic concepts of digital imaging not only theoretically but also visually by including six plates of digital artwork

Content based retrieval of PET neurological images

Medical image management has posed challenges to many researchers, especially when the images have to be indexed and retrieved using their visual content that is meaningful to clinicians. In this study, an image retrieval system has been developed for 3D brain PET (Position emission tomography) images. It has been found that PET neurological images can be retrieved based upon their diagnostic status using only data pertaining to their content, and predominantly the visual content. During the study PET scans are spatially normalized, using existing techniques, and their visual data is quantified. The mid-sagittal-plane of each individual 3D PET scan is found and then utilized in the detection of abnormal asymmetries, such as tumours or physical injuries. All the asymmetries detected are referenced to the Talairarch and Tournoux anatomical atlas. The Cartesian co- ordinates in Talairarch space, of detected lesion, are employed along with the associated anatomical structure(s) as the indices within the content based image retrieval system. The anatomical atlas is then also utilized to isolate distinct anatomical areas that are related to a number of neurodegenerative disorders. After segmentation of the anatomical regions of interest algorithms are applied to characterize the texture of brain intensity using Gabor filters and to elucidate the mean index ratio of activation levels. These measurements are combined to produce a single feature vector that is incorporated into the content based image retrieval system. Experimental results on images with known diagnoses show that physical lesions such as head injuries and tumours can be, to a certain extent, detected correctly. Images with correctly detected and measured lesion are then retrieved from the database of images when a query pertains to the measured locale. Images with neurodegenerative disorder patterns have been indexed and retrieved via texture-based features. Retrieval accuracy is increased, for images from patients diagnosed with dementia, by combining the texture feature and mean index ratio value

CPA firm technology planning guide

https://egrove.olemiss.edu/aicpa_guides/1443/thumbnail.jp