Automatic Caption Localization for Photographs on World Wide Web Pages

Bibliographic description
ROWE, Neil C.; FEW, Brian. Automatic Caption Localization for Photographs on World Wide Web Pages [on line]. Monterey: Department of Computer Science, U. S. Naval Postgraduate School, 1998. Available on: http://www.nps.navy.mil/Content/CS/ncrowe/marie/webpics.html"

Dublin Core
Title : Automatic Caption Localization for Photographs on World Wide Web Pages
Creator : Neil C. Rowe, Brian Frew
Subject : photograph retrieval / Photograph indexing / World Wide Web
Description : "Pictures, especially photographs, are one of the most valuable resources available on the Internet through the popular World Wide Web. Unlike text, most photographs are valuable primary sources of real-world data. Unlike conventional copy technology, photographs on the Web maintain their quality under transmission. Interest has increased recently in multimedia technology as its speed has improved by hardware and software refinements; photographs also benefit from these advances. This has meant that multimedia resources on the Web have grown quickly. For these reasons, indexing and retrieval of photographs is becoming increasingly critical."
Publisher : Department of Computer Science, U. S. Naval Postgraduate School, Monterey
Date : 1998
Type : Article
Format : HTML
Identifier : http://www.nps.navy.mil/Content/CS/ncrowe/marie/webpics.html
Source: http://www.nps.edu/
Language : En
Relation : -
Coverage : USA
Rights : U. S. Naval Postgraduate School

Abstract
"A variety of software tools index text of the World Wide Web, but little attention has been paid to the many photographs. We explore the indirect method of locating for indexing the likely explicit and implicit captions of photographs. We use multimodal clues including the specific words used, the syntax, the surrounding layout of the Web page, and the general appearance of the associated image. Our MARIE-3 system thus avoids full image processing and full natural-language processing, but shows a surprising degree of success. Experiments with a semi-random set of Web pages showed 41% recall with 41% precision for the task of distinguishing captions from other text, and 70% recall with 30% precision. This is much better than chance since actual captions were only 1.4% of the text on pages with photographs."

SPIRO: Slide and Photograph, Image Retrieval Online

Bibliographic description
ARCHITECTURE VISUAL RESOURCES LIBRARY. SPIRO [on line]. Berkeley: University of California, 11 december 2006. Available on: http://www.mip.berkeley.edu/query_forms/browse_spiro_form.html

Dublin Core
Title : SPIRO
Creator : Architecture Visual Resources Library, Department of Architecture, College of Environmental Design, University of California, Berkeley
Subject : Image database / architecture / Visual arts / City planning / Urban development
Description : "SPIRO is the visual online public access catalog to the 35mm slide collection of the Architecture Visual Resources Library (AVRL) at the University of California at Berkeley. The collection numbers over 250,000 slides and 20,000 photographs."
Publisher : University of California, Berkeley
Date : 2006-12-11
Type : Image Database
Format : HTML
Identifier : http://www.mip.berkeley.edu/query_forms/browse_spiro_form.html
Source: http://www.arch.ced.berkeley.edu/resources/archslides.htm
Language : En
Relation : http://www.mip.berkeley.edu/spiro/about.html
http://www.berkeley.edu/
Coverage : USA
Rights : Architecture Visual Resources Library

Abstract
"SPIRO permits access to the collection by seven access points which may be used independently or in combination:
historical period
place
personal name
object name
subject terms
source of image
image identification number
As of January 2004, SPIRO contained over 63,000 records linked to images, approximately 20% of AVRL's total slide collection. Thirty-three percent (33%) of the images in SPIRO come from images in books. These are produced in-house by copy stand photography under the fair use and educational copying provisions of the U.S. Copyright Law. Eleven percent (11%) of the images in SPIRO derive from copy stand photography from periodicals, also produced in-house. Thirty-eight percent (38%) of the images are donor- supplied, and eighteen percent (18%) are purchased from commercial slide vendors."

The Subject Analysis of Images: Past, Present and Future

Bibliographic description
WARDEN, Ginger; DUNBAR, Denise; WANCZYCKI, Catherine; O'HANLEY, Suanne. The Subject Analysis of Images: Past, Present and Future [on line]. University of British Columbia School of Library, 27th March 2002. Available on:
http://www.slais.ubc.ca/people/students/student-projects/C_Wanczycki/libr517/homepage.html

Dublin Core
Title : The Subject Analysis of Images: Past, Present and Future
Creator : Ginger Warden, Denise Dunbar, Catherine Wanczycki, Suanne O'Hanley
Subject : image collection / image classification / thesaurus / image indexing
Description : "The Art and Architecture Thesaurus (AAT) is a structured vocabulary that can be used to improve access to art, architecture, and material culture."
Publisher : University of British Columbia School of Library
Date : 2002-03-27
Type : Web site
Format : HTML
Identifier : http://www.slais.ubc.ca/people/students/student-projects/C_Wanczycki/libr517/homepage.html
Source: http://www.slais.ubc.ca/
Language : En
Relation : -
Coverage : UK
Rights : No

Extract
"Image collections exist for many purposes: medicine (ultrasounds, CAT scans), architecture (building plans), geography (aerial photos, maps), art (paintings, cartoons), business (trademarks), history (photographs). Some image collections are very large. The Getty Institute's Photo Study Collection, for example, has over two million photographs. Indexing collections of this size can be extremely time consuming, and unlike text, images cannot be searched by keyword. Many automatic indexing systems have been developed, but what computers can currently extract from images are "mostly low-level features" (Rui, 1999) like color, shape, and texture. Research on the information needs of users, and on human perception of images may, in time, contribute the knowledge needed to produce the most precise and efficient retrieval systems possible.

In the meantime, librarians contending with image collections have to make decisions about how best to provide access to them. Currently, there is no universal consensus in libraries. In a survey of 58 libraries in the U.K., (Graham, 1999) the clear majority of respondents employed in-house methods of classifying and indexing their collections, rather than relying on publicized schemes, such as the AAT (Art and Architecture Thesaurus), LCTGM (Library of Congress Thesaurus for Graphic Materials), and LCSH (Library of Congress Subject Headings). This is likely the result of tradition. Curators of image collections were left to their own devices for most of the century, insofar as subject headings for images went, while LCSH concentrated on primarily text-based materials. Many different thesauri were developed by individuals or groups of individuals to deal with particular collections but efforts to create a universally acceptable indexing language for images has only been a point of interest in the past 30 years or so, with the increasing volume of available images and the desire for increased resource-sharing between institutions.

The AAT and LCTGM are presently the two most widely accepted vocabularies for use with image collections. Their development, structure and scope are the main focus of this website. Subject headings from each are applied to several types of images by way of example. We also look to the past and future of subject access to images by surveying both the methods librarians have used in the past (and are still using today to some extent) and the methods that are currently being developed (and to some extent already in place)."

Iconclass: iconographic classification system

Bibliographic description
Iconclass: iconographic classification system. The Netherlands Institute for Scientific Information Services, 21 october 2003. Available on: http://www.niwi.knaw.nl/en/geschiedenis/projecten/iconclass/

Dublin Core
Title : Iconclass: iconographic classification system
Creator : ?
Subject : Iconclass / image classification / thesaurus
Description : It's a" classification system for standardized description of the contents of visual documents."
Publisher : the Netherlands Institute for Scientific Information Services (NIWI)
Date : 2003-10-21
Type : article
Format : HTML
Identifier : http://www.niwi.knaw.nl/en/geschiedenis/projecten/iconclass/
Source: http://www.niwi.knaw.nl/nl/
Language : En
Relation : http://www.iconclass.nl/
Coverage : Netherland
Rights : -

Abstract
Iconclass is a classification system for standardized description of the contents of visual documents. [...]
Iconclass is a collection of ready-made classification codes called notations, used to define objects, persons, events, situations, abstract ideas and other potential subjects of visual documents. The approximately 28,000 definitions are arranged in hierarchical order and divided into ten main classes. Some classes are designed for the description of specific subjects, in particular biblical, mythological and literary themes. These are used mainly in art-historical context. Others, containing general subjects, constitute a self-sufficient system offering a place to every subject and activity on earth.

IPTC Standard

Bibliographic description
The IPTC-NAA standards [on line]. Controlled Vocabulary. Available on:
http://www.controlledvocabulary.com/imagedatabases/iptc_naa.html

Dublin Core
Title : The IPTC-NAA standards
Creator : ?
Subject : metadata / IPTC / image description / image database
Description : "A controlled vocabulary can be useful in describing images and information when organizing and classifying content for image databases."
Publisher : Controlled Vocabulary
Date : ?
Type : Article
Format : HTML
Identifier : http://www.controlledvocabulary.com/imagedatabases/iptc_naa.html
Source : http://www.controlledvocabulary.com/
Language : En
Relation : -
Coverage : ?
Rights : -

Extract
Each image file can be saved using Adobe Photoshop with this text information embedded within the file. Anyone that's worked around newspapers, with digital images or image databases for a while has probably heard the acronyms IPTC or IPTC-NAA tossed around, usually when discussing the use of the File Info feature of photoshop. But few understand what they mean or stand for. The short story is that IPTC, the International Press Telecommunications Council, was one of the groups responsible for encouraging the standards necessary to“marry” the text information describing an image with the image data itself. The NAA is the Newspaper Association of America (formerly ANPA), and they also have been responsible for developing standards for exchanging information between news operations, including information used to describe images. [...]
Standards regarding metadata for news images have evolved over time, beginning in the 1970's when some were first issued as“guidelines.” However, most of these efforts were regional in nature, and focused on text. As news organizations moved from manual typewriters to CRTs (Cathode Ray Tubes) and VDTs (Video Display Terminals) these standards were revised and became more specific. Only later, as the world embraced the web, did the standards begin to address multimedia content.
In 1979, the International Press Telecommunications Council (IPTC) approved its first news exchange standard IPTC 7901. This provided metadata and content in plain text only; the only delimiters allowed were spaces and line breaks...

Photo classification by integrating image content and camera metadata

Bibliographic description
BOUTELL, M., LUO, Jiebo. Photo classification by integrating image content and camera metadata. Rochester University, MN, USA: Department of Computer Science, 23 august 2004. Available on: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1333918

Dublin Core
Title : Photo classification by integrating image content and camera metadata
Creator : Boutell, M. Jiebo Luo
Subject : Image classification / content-based /metadata / semantic classification
Description :
Publisher : IEEE EXPLORE
Date : 2004-08-23
Type : article
Format : PDF
Identifier : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1333918
Source : http://ieeexplore.ieee.org/Xplore/guesthome.jsp
Language : En
Relation : -
Coverage : USA
Rights : Copyright 2006 IEEE

Abstract
Despite years of research, semantic classification of unconstrained photos is still an open problem. Existing systems have only used features derived from the image content. However, Exif metadata recorded by the camera provides cues independent of the scene content that can be exploited to improve classification accuracy. Using the problem of indoor-outdoor classification as an example, analysis of metadata statistics for each class revealed that exposure time, flash use, and subject distance are salient cues. We use a Bayesian network to integrate heterogeneous (content-based and metadata) cues in a robust fashion. Based on extensive experimental results, we make two observations: (1) adding metadata to content-based cues gives highest accuracies; and (2) metadata cues alone can outperform content-based cues alone for certain applications, leading to a system with high performance, yet requiring very little computational overhead. The benefit of incorporating metadata cues can be expected to generalize to other scene classification problems.

CIRES: Content Based Image Retrieval System

Bibliographic description
IQBAL, Qasim; AGGARWAL, J.K. CIRES: A system for Content Based Retrieval in digital image libraries [on line]. Singapore: Invited session on Content Based Image Retrieval: Techniques and Applications, International Conference on Control, Automation, Robotics and Vision (ICARCV), 2 december 2002. Available on: http://amazon.ece.utexas.edu/~qasim/papers.htm

Dublin Core
Title : CIRES: Content Based Image Retrieval System
Creator : Qasim Iqbal, J. K. Aggarwal
Subject : image retrieval, content based, retrieval system, CIRES
research, CIRES
Description : This document is a powerful tool om line for retrieval in digital image libraries
Publisher : International Conference on Control, Automation, Robotics and Vision (ICARCV)
Date : 2002-12-02
Type : Conference
Format : PDF
Identifier : http://amazon.ece.utexas.edu/~qasim/papers.htm
Source : http://amazon.ece.utexas.edu/~qasim/
Language : En
Relation : -
Coverage : USA
Rights :

Abstract
This papers presents CIRES, a new online system for content-based retrieval in digital image libraries. Contentbased image retrieval systems have traditionally used color and texture analyses. These analyses have not always achieved adequate level of performance and user satisfaction. The growing need for robust image retrieval systems has led to a need for additional retrieval methodologies. CIRES addresses this issue by using image structure in addition to color and texture. The efficacy of using structure in combination with color and texture is demonstrated.

Retrieval of Pictures Using Approximate Matching

Bibliographic description
PRASAD SISTLA, A; YU, Clement. Retrieval of Pictures Using Approximate Matching [on line]. University of Illinois: Departement of Electrical engeneering and computer science , 1995. Available on: http://citeseer.ist.psu.edu/sistla95retrieval.html

Dublin Core
Title : Retrieval of Pictures Using Approximate Matching
Creator : A. Prasad Sistla, Clement Yu
Subject : picture retrieval / image database
Description : A description of a general-purpose pictorial retrieval system based on approximate matching.
Publisher : Departement of Electrical engeneering and computer science, University of Illinois
Date : 1995
Type : Book extract
Format : PDF
Identifier : http://citeseer.ist.psu.edu/sistla95retrieval.html
Source : http://citeseer.ist.psu.edu/
Language : En
Relation : -
Coverage : USA
Rights : Copyright Penn State and NEC

Abstract
We describe a general-purpose pictorial retrieval system based on approximate matching. This system accommodates pictorial databases for a broad class of applications. It consists of tools for handling the following aspects--- user interfaces, reasoning about spatial relationships, computing degrees of similarity between queries and pictures. In this paper, we briefly describe the model that is used for representing pictures/queries, the user interface, the system for reasoning about spatial relationships, and the methods employed for computation of similarities of pictures with respect to queries.

Picture Retrieval Systems: A Unified Perspective and Research Issues

Bibliographic description
Venkat N. Gudivada, Vijay V. Raghavan. Picture Retrieval Systems: A Unified Perspective and Research Issues [on line]. Ohio University: Department of Computer Science, The Center for Advanced Computer Studies, 1995. Available on: http://citeseer.ist.psu.edu/gudivada95picture.html

Dublin Core
Title : Picture Retrieval Systems: A Unified Perspective and Research Issues
Creator : Venkat N. Gudivada, Vijay V. Raghavan
Subject : picture retrieval / image database / Picture Retrieval System
Description :
Publisher : Department of Computer Science, The Center for Advanced Computer Studies, Ohio University
Date : 1995
Type : article
Format : PDF
Identifier : http://citeseer.ist.psu.edu/gudivada95picture.html
Source : http://citeseer.ist.psu.edu/
Language : En
Relation : -
Coverage : USA
Rights : Copyright Penn State and NEC

Abstract
Picture Retrieval (PR) problem is concerned with retrieving pictures
that are relevant to users' requests from a large collection of
pictures, referred to as the picture database. We use the term
picture in a very general context to refer to different types of
images originating in disparate application areas. The sources for
these images range from satellites, diagnostic medical imaging,
architectural and engineering drawings, geographic maps, mug-shot
images of criminals, to family photographs and portraits. A computer
system that facilitates picture retrieval is referred to as the
Picture Retrieval System (PRS). The application areas that consider
picture retrieval as a principal activity are both numerous and
disparate. As diverse as the application areas are, there seems to be
no consensus as to what a picture retrieval system really is.
Consequently, the features of the existing picture retrieval systems
have essentially evolved from domain specific considerations.

Real-Time Computerized Annotation of Pictures

Bibliographic description
LI, Jia; Z.WANG, James. Real-Time Computerized Annotation of Pictures [on line]. The Pennsylvania State University, University Park, 25 July 2006. Available on: http://infolab.stanford.edu/~wangz/project/imsearch/ALIP/ACMMM06/li06.pdf

Dublin Core
Title : Real-Time Computerized Annotation of Pictures
Creator : Jia Li and James Z. Wang
Subject : digital picture / indexing / automatic indexing
Description : An article about automated annotation of digital pictures and the web site ALIPR (Automatic Linguistic Indexing of Pictures).
Publisher : http://infolab.stanford.edu/
Date : 2006-07-25
Type : article
Format : PDF
Identifier : http://infolab.stanford.edu/~wangz/project/imsearch/ALIP/ACMMM06/li06.pdf
Source : http://infolab.stanford.edu/
Language : En
Relation : http://www.alipr.com/, http://wang.ist.psu.edu/docs/home.shtml
Coverage : USA
Rights : ACM Multimedia Conference

Abstract
Automated annotation of digital pictures has been a highly challenging problem for computer scientists since the invention of computers. The capability of annotating pictures by computers can lead to breakthroughs in a wide range of applications including Web image search, online picture-sharing communities, and scientific experiments. In our work, by advancing statistical modeling and optimization techniques, we can train computers about hundreds of semantic concepts using example pictures from each concept. The ALIPR (Automatic Linguistic Indexing of Pictures - Real Time) system of fully automatic and high speed annotation for online pictures has been constructed. Thousands of pictures from an Internet photo-sharing site, unrelated to the source of those pictures used in the training process, have been tested. The experimental results show that a single computer processor can suggest annotation terms in real-time and with good accuracy.

Museum photo collections

Bibliographic description
CORBAL, Marie. Museum photo collections [on line]. IUT Michel de Montaigne, 2006. Available on: http://www.iut.u-bordeaux3.fr/doc/sitos2006/MuseumPhotography/Welcome.htm

Dublin Core
Title : Museum photo collections
Creator : Marie Corbal
Subject : Documentary processing / Museum photograph
Description : This site present a collection of links on the material and intellectual processing of museum photographs. There are some definitions.
Publisher : IUT Michel de Montaigne
Date : 2006
Type : Web site
Format : HTML
Identifier : http://www.iut.u-bordeaux3.fr/doc/sitos2006/MuseumPhotography/Welcome.htm
Source : http://www.iut.u-bordeaux3.fr/site/jsp/site/Portal.jsp
Language : Fr
Relation : http://www.iut.u-bordeaux3.fr/doc/sitos2006.htm
Coverage : France
Rights : IUT Michel de Montaigne

Extract
"DOCUMENTARY PROCESSING OF PHOTOGRAPHY


MATERIAL PROCESSING

Stocktaking
The stocktaking relies on international standard bibliographic description (ISBD) publicated by the International Federation of Library Associations and Institutions (IFLA).

Recording
The documentary activity is written on a specific project which enables it to record. There are compulsory information such as the number of recordings, the date of the shot, the copyright, the name of photographer, the support, the format, the number of the shot and the legend with the localization.

Watermarking
It's an ink or a computing plug which underlines compulsory datas such as the copyright, the address of the institution, the author, a brief legend, and the number of the negative.


INTELLECTUAL PROCESSING

Legend
The legend can either be a piece of information, a commentary or a specific annotation. It is always in relation to the photography itself. It mentions the place, the date of the shot and the subject of the photography. In short it enables the researcher to exploit and to organize the collection.

Indexing
It is a device which enables to condense the information available on the photograph will were help of specific vocabulary such as iconographic thesaurus, free indexing, indexing language and classifying language. It enables to choose a precise word corresponding to the needs of the service. There is a link between the photography and the word choosen. For example, there is system of indexing such as ICONCLASS, GARNIER, RAMEAU and ICONOS. They are made for description of the photography."

Tribune company photo archiving task force : keys words (enhancement terms), and photo type words for digital photo archives

Bibliographic description
SLA NEWS DIVISION. Tribune company photo archiving task force : keys words (enhancement terms), and photo type words for digital photo archives, usage guidelines and alternatives [on line]. SLA News division, July 1995. Available on: http://www.ibiblio.org/slanews/conferences/sla1998/tribusage.html

Dublin Core
Title : Tribune company photo archiving task force : keys words (enhancement terms), and photo type words fer digital photo archives, usage guidelines and alternatives
Creator : SLA News division
Subject : Photography / Indexing / Keywords / Index terms / Digital photograph
Description : It's a keywords list for indexing press photos
Publisher : ibiblio.org
Date : 1995-07
Type : Guide
Format : HTML
Identifier : http://www.ibiblio.org/slanews/conferences/sla1998/tribusage.html
Source : ibiblio.org
Language : En
Relation : 1998 SLA News Division Preliminary Program
Coverage : USA
Rights : No

Extract
"ABUSE
ABORTION
ACCIDENT
ADVERTISING
AGRICULTURE - see also GARDEN, FARM, RANCH.
AIDS - the disease, not implements that assist. Use with DISEASE.
not air force; use MILITARY.
AIR
AIRCRAFT - use for helicopters, commercial airliners, bombers, spy planes, and inflatable transportation vehicles, such as weather balloons, the Goodyear blimp, etc. See also SATELLITE, SPACECRAFT.
ALCOHOL - see also BEVERAGE, WINE.
not alien; use IMMIGRANT, MIGRANT, REFUGEE, TRAVEL.
not amusement park; use ATTRACTION.
ANATOMY - see also BODY, NUDITY.
ANIMAL
ANNIVERSARY
ANTIQUE
APARTMENT
APPLIANCE - see also EQUIPMENT.
ARCHAEOLOGY
not archery; use ** in supplemental category field.
not archive; use LIBRARY or MUSEUM.
ARCHITECTURE
not army; use MILITARY.
not arms or armament; use WEAPON.
not arms control; use WEAPON and CONTROL.
ARREST
ART - a photo of a painting, collage, etc.; see also SCULPTURE.
ASSASSINATION
ASTRONAUT
ASTRONOMY - includes asteroids, comets, galaxies, planets (except earth), stars, and other celestial objects. See also ECLIPSE, MOON, SUN.
ATHLETE - use to distinguish between persons with same or similar name.
ATTRACTION - A place or event to which a tourist might want to go.
AUCTION
AUDIO - use with EQUIPMENT for audio equipment.
AUTO
AUTUMN
AVALANCHE
AWARD - includes medal, trophy, certificate, honorary degree, national honor.

BABY - includes last trimester of pregnancy through age 2; Age 3 to teens use CHILD; then TEENAGER or JUVENILE, as appropriate.
not ballet; use DANCE.
BALLOON - toy; use AIRCRAFT for inflatable air transportation vehicles and weather balloons.
not band; use MUSIC and GROUP.
BANK - includes depository, S&L, credit union, etc.
BAR - see also RESTAURANT..."

Image classification for content-based indexing

Bibliographic description
VAILAYA, Aditya; FIGUEIREDO, Mario A . T; JAIN, Anil K; ZHANG, Hong-Jiang. Image classification for content-based indexing [on line]. IEEE EXPLORE, january 2001. Available on: http://citeseer.ist.psu.edu/correct/686126

Dublin Core
Title : Image classification for content-based indexing
Creator : Aditya Vailaya, Mario A. T. Figueiredo, Anil K. Jain, Hong-Jiang Zhang
Subject : Image classification / Content-based / Indexing
Description : "Grouping images into (semantically) meaningful categories using low-level visual features is a challenging and important problem in content-based image retrieval."
Publisher : IEEE EXPLORE
Date : 2001-01
Type : article
Format : HTML
Identifier : http://citeseer.ist.psu.edu/correct/686126
Source : http://citeseer.ist.psu.edu/
Language : En
Relation : http://citeseer.ist.psu.edu/nrelated/1894793/686126
Coverage : USA
Rights : Copyright 2001 IEEE

Extract
"Grouping images into (semantically) meaningful categories using low-level visual features is a challenging and important problem in content-based image retrieval. Using binary Bayesian classifiers, we attempt to capture high-level concepts from low-level image features under the constraint that the test image does belong to one of the classes. Specifically, we consider the hierarchical classification of vacation images; at the highest level, images are classified as indoor or outdoor; outdoor images are further classified as city or landscape; finally, a subset of landscape images is classified into sunset, forest, and mountain classes. We demonstrate that a small vector quantizer (whose optimal size is selected using a modified MDL criterion) can be used to model the class-conditional densities of the features, required by the Bayesian methodology. The classifiers have been designed and evaluated on a database of 6931 vacation photographs. Our system achieved a classification accuracy of 90.5% for indoor/outdoor, 95.3% for city/landscape, 96.6% for sunset/forest and mountain, and 96% for forest/mountain classification problems. We further develop a learning method to incrementally train the classifiers as additional data become available. We also show preliminary results for feature reduction using clustering techniques. Our goal is to combine multiple two-class classifiers into a single hierarchical classifier."

Image Archiving

Bibliographic description:
BAUMGART, Jessica. Image Archiving [on line]. SLA News division, 3th march 2003. Available on: http://www.ibiblio.org/slanews/conferences/sla1996/ce.htm

Dublin Core:
Title : Image Archiving
Creator : Jessica Baumgart
Subject : Image / image archiving
Description : Conference by Rande Anmuth Simson on June 9, 1996 about Practical applications of digital news libraries.
Publisher : SLA News division
Date : 2003-03-23
Type : Conference
Format : HTML
Identifier : http://www.ibiblio.org/slanews/conferences/sla1996/ce.htm
Source : http://www.ibiblio.org/
Language : En
Relation : http://www.ibiblio.org/slanews/conferences/sla1996/index.htm
Coverage : USA
Rights : Jessica Baumgart

Extract

"In our most recent release of the AP archive we have made some major changes. One was to add the Personal Library Software database which brings full text searching capability as well as relevance ranking on hits, fuzzy term searching and related term searching. PLS also provides us with links to other PLS text databases. We feel PLS has an easier to use and faster search engine than the relational database that Informix provided the archive.

Another development was to make the Archive a Web server. This enables us to use Netscape as client software to compliment the Picture desk software which is still available. Netscape is truly cross-platform and can be used on Macs, PCs, Sun or IBM unix clients via Intranet and Internet.. We chose to use an HTML browser because of the programming possibilities with Java Script and its easy to use interface. Netscape provides the AP Preserver archive with yet another familiar interface which requires minimal training for the newspaper staffs to use.

We have consolidated hardware choices for our system to the latest, fastest and less expensive RS6000 PowerPC cpus, which resulted in a price reduction for the archive.

A most exciting development is a cooperation between AP and DataTimes to link the Preserver with EyeQPublisher, a text archive. This combination will allow users to search text, graphics and images from a single Netscape client. Rather than re-invent the wheel AP decided to rely on a text vendor to handle the text end of the archive. Oklahoma City will be our beta site for the combined text and image archives. I'm sure Carol Campbell will be happy to keep you all informed of developments on that end.

One of our Preserver sites, the Minneapolis Star-Tribune, developed a photo assignment tracking database which compliments the Preserver. Assignment information is parsed into the appropriate fields when the image enters the archive, saving some of the indexing work. The AP and the Minneapolis Star-Tribune have decided to make this assignment module available to other newspapers with Preservers and those without as well.

Our future plans for the archive include integration with the AP server picture desk and true support for multimedia. We are watching developments with Digital Video Disk as an optional storage media."

Text and Photo : database enhancement terms

Bibliographic description:
WILLEN BROWN, Stéphanie. Text and Photo : database enhancement terms [on line]. Special Libraries Association News Division, 1st september 2001. Available on: http://www.ibiblio.org/slanews/archiving/terms/index.htm

Dublin Core:
Title : Text and Photo : database enhancement terms
Creator : Stephanie Willen Brown
Subject : enhancement terms / indexation / newspaper
Description : Links to database enhancement terms used in newspaper libraries across the United States.
Publisher : www.ibiblio.fr
Date : 2001-09-04 (last updated)
Type : Text
Format : HTML
Identifier : http://www.ibiblio.org/slanews/archiving/terms/index.htm
Source : http://www.ibiblio.org
Language : En
Relation : -
Coverage : USA
Rights : Amy Disch


Extract

"These pages provide links to database enhancement terms used in newspaper libraries across the United States.
Newspaper librarians use enhancement terms to assist in the full-text retrieval of news articles and photos from large databases.
Enhancement terms are also known as keywords or subjects.
Chicago Tribune
Tribune Company Photo Archiving Task Force
Detroit Free Press
The News & Observer, Raleigh, N.C.
Sacramento Bee
St. Petersburg Times
Spokane Spokesman-Review 
Springfield (MA) Union-News "

Indexing Photographs

Bibliographic reference
WILLEN BROWN, Stephanie. Indexing photographs [on line]. Springfield (Mass.): Union-News and Sunday Republican, Visual Edge '98 Archive Program, 4th September 2001. Available on: http://www.ibiblio.org/slanews/archiving/VE98/presentation.htm


Dublin Core
Title : Indexing photographs
Creator : Stephanie Willen Brown
Subject : newspaper photograph / indexing / keyword / free text
Description : It's about "newspaper photograph indexing, the use of keywords or free text to accomplish the indexing, and several examples of indexed newspaper pictures."
Publisher : http://www.ibiblio.org/
Date : 2001-12-04
Type : Conference
Format : HTML
Identifier : http://www.ibiblio.org/slanews/archiving/VE98/presentation.htm
Source : http://www.ibiblio.org/
Language : En
Relation : http://www.ibiblio.org/slanews/archiving/VE98/indexing.htm
Coverage : USA
Rights : Amy Disch


Extract
"Introduction
It is essential to have several ways to define the activity a photograph describes because describing the exact meaning of a picture is very difficult. When indexing works of art or music, this is especially tough, because only terms added by a librarian can be used to search the database. Newspaper photograph databases are easier to search because the cutline field is a wonderful source of information. The cutline usually has most of the information relevant to the image, including names of subjects, location, and a description of the activity.

In this presentation, I will (briefly!) discuss newspaper photograph indexing, the use of keywords or free text, and review several examples of indexed newspaper pictures. I have pulled 18 photographs from the Springfield Union-News to demonstrate how both keywords and free text indexing might be applied to a variety of situations.

Different Kinds of Searching
Searching the cutlines of hundreds of thousands of photographs to retrieve one of the principal of a grammar school would be relatively easy: the searcher – librarian, reporter, editor, photographer – would simply type in the name and a small number of photographs would likely be retrieved (assuming the person is not a trouble maker or married to a prominent figure). However, searching for an appropriate photograph of the mayor of the dominant city in a newspaper’s coverage area, Springfield in our case, would likely retrieve hundreds of images.

And what if you needed photographs of golf courses to accompany a story about the proliferation of golf courses in your area? You would have to remember the names of all the golf courses in the area and do a complicated, nested search. — Franconia, Crestview, the Orchards — You might forget the name of one or two of them, or you might retrieve photographs of events taking place at the "19th hole" of an area course.

A further curve thrown into the photo indexing mix is that different types of people — photographers, librarians, editors, and the general public — will need to search the database. Each group will need to retrieve different kinds of pictures:

o photographers might want to see if a particular scene had already been shot; (images of Taste of Holyoke, for example)
librarians would be looking for a photograph of a prominent politician;
Living/Arts editors might want a picture of last year’s big event (Shriner’s auto show) for an advance of this year’s event;
the general public might want a photograph of little Janey playing field hockey.

Indexing is the Answer
Applying subject terms to each photograph will greatly aid in retrieval. Ideally, each image will be assigned two to five subjects, addressing the central news aspect of the picture. This results in a richer description of a photograph. Indexers should add words that are not in the cutline to enhance the value of the subject field. A picture of a defendant in a murder trial, for example, would be assigned the keywords Murder and Trial. Either one used by itself is not enough to describe a photo of a defendant charged of murder who is on the witness stand, though both are correct and useful. But together, they accurately express the concepts demonstrated in the photograph.

Keywording vs. Free text
We will discuss two different ways of adding subject ideas to a photograph database: keywording and free text. I’ll describe, and show examples, of each.

"Keywording" refers to adding terms from a controlled vocabulary to a database of photographs to aid later retrieval. The most important component of keywording is the notion of a controlled vocabulary, a specific set of words from which index terms can be taken. Keywording is the a traditional means of indexing photographs, and is taught as Indexing in library school. A photograph of children on a swing, for example, might be given the keywords CHILD; PLAYING; and SUMMER.

"Free text" indexing, on the other hand, does not rely on a controlled vocabulary. Instead, it is more like free association: the indexer looks at the photograph and uses her imagination to describe what it is "about." A photograph of children on a swing, for example, could be "about" a hot summer afternoon; children or kids; swinging or playing; brothers, perhaps, if the children are related; smiling or laughing; and having fun."

Glossary English/French

Photography
Definition: “The art or process of producing images by the action of light on surfaces sensitized by chemical processes.”
Source: http://www.ncpublicschools.org/curriculum/artsed/scos/visualarts/vglossary

Photographie
Définition: "Ensemble des techniques permettant d'obtenir des images permanentes grâce à un dispositif optique produisant une image réelle sur une surface photosensible."
Source: Trésor de la langue Française


Librarianship
Definition: “The application of theories, principles, and techniques to the collection, preservation, organization, and use of recorded communications.”
Source: http://www.seattlecentral.org/faculty/jshoop/glossary.html

Bibliothéconomie
Définition: "Science, techniques et activités relatives à l'organisation, la gestion, la législation et la règlementation des bibliothèques."
Source: Vocabulaire de la documentation/ADBS. 2004.


Image processing
Definition: “Encompasses all the various operations which can be applied to photographic or image data. These include, but are not limited to image compression, image restoration, image enhancement, preprocessing, quantization, spatial filtering and other image pattern recognition techniques.”
Source: http://www.gaf.de/presshelp/glossary/p81.htm

Traitement d’image
Définition: "Ensemble de fonction de calcul et de manipulation d'images numériques visant à améliorer leur visualisation. Les principales fonctions sont la restauration d'images dégradées, l'amélioration de certaines caractéristiques (contraste, élimination du flou), la mise en valeur d'éléments spécifiques (recherche de contours ou de plages de couleur, calcul de surfaces) et la classification."
Source: Vocabulaire de la documentation/ADBS. 2004.


Still image
Definition: "Nonmoving visual information, i.e., fixed images, such as graphs, drawings, and pictures."
Source: http://www.atis.org/tg2k/_still_image.html

Image fixe
Définition: "Représentation généralement en 2 dimensions, opaque (par exemple estampe, dessin, épreuve photographique) ou translucide (par exemple diapositive, négatif), destinée à être regardé directement ou projetée sans mouvement à l'aide d'un instrument optique."
Source: Vocabulaire de la documentation/ADBS. 2004.


Physical document processing
Definition: "Methods, procedures and tools used to treat(handle), to arrange, to preserve and to store documents as support, whatever is this one. "
Source: Vocabulaire de la documentation/ADBS. 2004.

Traitement physique des documents
Définition: "Méthodes, procédures et outils utilisés pour traiter, ranger, conserver et stocker des documents en tant que support, quel que soit celui-ci."
Source: Vocabulaire de la documentation/ADBS. 2004.


Intellectual document processing
Definition: "census, classification, description."
Source: http://cat.inist.fr/?aModele=afficheN&cpsidt=2000296

Traitement intellectuel des documents
Définition: "Recensement, classement, description."
Source: http://cat.inist.fr/?aModele=afficheN&cpsidt=2000296


Image analysis
Definition: “Image analysis is the extraction of useful information from images; mainly from digital images by means of digital image processing techniques. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person by its face.”
Source: http://en.wikipedia.org/wiki/Image_analysis

Analyse d'image
Définition: "L'analyse d'image a pour but d'extraire des informations qualitatives ou quantitatives d'une image ou d'un ensemble d'images. Cela requiert la mise en oeuvre et l'enchaînement d'un certain nombre de processus, comme l'identification des différents objets ou composants de l'image encore appelé segmentation, le calcul de leurs relations topologiques ou géométriques, l'estimation de mesures globales ou locales, et le cas échéant la caractérisation de ces objets."
Source: http://www.labri.fr/equipes/ImageSon/img_analyse/img_analyse.php


Picture indexing
Definition: “Automatic image annotation (also known as automatic image tagging) is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision techniques is used in image retrieval systems to organize and locate images of interest from a database.”
Source: http://en.wikipedia.org/wiki/Automatic_image_annotation

Indexation d' image
Définition: "Représentation, par les éléments d'un langage documentaire ou naturel, des données résultant de l'analyse du contenu d'un document ou d'une partie d'un document, généralement en vue d'en faciliter la recherche."
Source: Grand dictionnaire terminologique


Picture digitization
Definition: “Transformation of analog data into digital data for computer storage and processing.”
Source: http://www.startphoto.com/learn/glossary/glossary_di-dn.htm

Numérisation d'image
Définition: "Transformation, en format numérique, d'une image enregistrée originalement sur une épreuve photographique."
Source: http://www.ccrs.nrcan.gc.ca/glossary/index_f.php?id=224


Image classification
Definition: “Image classification is the process of creating thematic maps from satellite imagery. A thematic map is an informational representation of an image which shows the spatial distribution of a particular theme. Themes can be as diversified as their areas of interest. Example of themes are soil, vegetation, water depth, and atmosphere. Inside a theme, there can be defined subthemes, and thus the process of classification needs to become more refined.”
Source: http://aria.arizona.edu/courses/tutorials/class/html/classwhyp1.html

Classification des images
Définition: "Action de distinguer par classes, par catégories, des documents selon un certain ordre."
Source: Grand dictionnaire terminologique


Picture retrieval
Definition : “An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, or descriptions to the images so that retrieval can be performed over the annotation words.”
Source : http://en.wikipedia.org/wiki/Image_retrieval

Recherche d'image
Définition: "Consultation des instruments de travail et des fonds d'archives correspondants dans un but d'information."
Source: Grand dictionnaire terminologique