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    <article-meta>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Pramod Jain Innovative Decision Technologies, Inc.</institution>
          <addr-line>9000 Cypress Green Drive, Jacksonville, FL 32256</addr-line>
          <country country="US">USA</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>In this paper, we describe a tool for rich annotation of images. This tool allows creation of graphical annotations to identify and describe features in images. It also provides the capability to then catalog the annotation layer in metadata repositories. Application of the annotation tool to describe satellite images in the areas of meteorology and vegetation will be presented.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Annotations</kwd>
        <kwd>Scalable vector graphics</kwd>
        <kwd>SVG</kwd>
        <kwd>Rich annotations</kwd>
        <kwd>Images</kwd>
        <kwd>Attributes</kwd>
        <kwd>Metadata</kwd>
        <kwd>DLESE (Digital Library for Earth Science Education)</kwd>
        <kwd>NASA-GCMD (Global Change Master Directory)</kwd>
        <kwd>content-based metadata</kwd>
        <kwd>XIMA (XML for Image and Map Annotations)</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>RICH ANNOTATIONS</title>
      <p>Rich annotation (RA) is a combination of a) graphical
drawing or marking to identify the location and geometry
of a feature in an image and b) attributes or properties to
describe the annotated feature. RA is created in a
transparent layer placed on top of the image using Scalable
Vector Graphics (SVG, a World Wide Web Consortium’s
standard for 2-D graphics on the web). The transparent
layer is called an annotation layer, and it can contain
several annotated features. We have developed Rich
Annotation Service for Images (RASI), a web-based tool to
create rich annotations of images. Rich annotation is a
fusion of a graphical marker (to identify a feature) and a
structured object (to describe the feature) that contains
attribute names and attribute values, this is the reason for
calling it a “rich” annotation.</p>
    </sec>
    <sec id="sec-2">
      <title>RICH ANNOTATION SERVICE FOR IMAGES (RASI)</title>
      <p>RASI is a web-based application for creating rich
annotations of images, it may be accessed at
http://www.indent.org/rasi.htm. The drawing capabilities
in the browser are programmed in Scalable Vector
Graphics (SVG, a World Wide Web Consortium standard
for 2-D graphics on the web). See Figure 1 for a screen
shot of RASI.</p>
      <p>RASI contains an annotation canvas, an annotation toolbar
and section to manage properties. In the annotation toolbar,
a palette of annotation markers is available to draw
freeform or place icons in the annotation canvas. When a
feature is annotated in an image using an annotation
marker, a rich annotation is created. This rich annotation
object contains the geometry of the annotation marker and
a set of properties. See Figure 2 for relationship between
the various entities in RASI.</p>
      <p>As an example consider an Infrared (IR) image of a storm
with features like cold front, warm front, occluded front
and low pressure point. These features are annotated with
appropriate annotation markers. Cold front, warm front
and occluded front feature have a property called
“precipitation,” and low pressure point has properties:
surface pressure, surface temperature, precipitation, and
cloud top temperature. The annotation markers used for
the features are: cold front is drawn using the blue line
with triangles, warm front with the red line with semicircle,
and low pressure point is an icon with letter L in the center.
The RASI tool is customizable to other domains—user
with appropriate authorization can create a new problem
domain, define new features for the domain, and create
annotation marker and annotation properties for the new
features.</p>
      <p>The process of creating annotations is the following, user:
picks an annotation tool based on the feature they want to
annotate; creates an annotation to identify the feature;
chooses the created annotation and assigns values to the
properties associated with the feature; add more properties
if required; create more features on the same annotation
layer; saves the annotation layer; creates metadata for the
annotation layer and submits to DLESE or NASA-GCMD.</p>
      <sec id="sec-2-1">
        <title>Image</title>
        <p>0…*
Annotation
Layer</p>
        <p>0…*</p>
      </sec>
      <sec id="sec-2-2">
        <title>Rich</title>
        <p>Annotation
Ù Collection of
Annotated Features
Ù Annotated
Features
1</p>
      </sec>
      <sec id="sec-2-3">
        <title>Annotation Marker</title>
        <p>0…*
Annotation</p>
        <p>Properties
The three components of its technical architecture are (see
Figure 3): i) User-Agent, which includes HTML,
Javascript, SVG and XML files that are delivered to the
browser or to a metadata repository; ii) Middle-tier, which
is ASPIRE (http://www.indent.org/aspire.htm, a Java-based
Commercial Off The Shelf product of Innovative Decision
Technologies, inc.) and is used to process SVG-XML data
from browser and store into database, extract relational
data from database and transform into SVG-XML, and
metadata repository specific XML formats; iii) Database.
The middle-tier generates the SVG, HTML and XML files
based on templates that contain Aspire specific
replacement, loop and if tags.</p>
        <p>RASI also contains a search facility that allows users to
search for images based on advanced queries like:
Find an image with keywords = “cold front” AND (cloud
top temperature &lt; -50 Celsius OR pressure &lt; 970 milli
bars).</p>
      </sec>
      <sec id="sec-2-4">
        <title>Metadata Services</title>
        <p>Annotation
Database
RASI running in
browser with
SVGViewer plug-in
Web
Server</p>
      </sec>
      <sec id="sec-2-5">
        <title>Middle-tier: Aspire/J2EE</title>
        <p>XML,
SVG,
HTML</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>CONCLUSIONS</title>
      <p>RASI has been built for creating rich annotations for
images. Several projects have been created in areas of
meteorology, vegetation and others to allow users to
capture knowledge in a graphical manner on the image. In
addition, this knowledge is used to generate metadata for
images</p>
    </sec>
    <sec id="sec-4">
      <title>ACKNOWLEDGMENTS</title>
      <p>We thank NASA for partially funding the development of
RASI; NASA-GCMD and DLESE for cataloging the
metadata records from RASI.</p>
      <p>Annotation Properties</p>
    </sec>
  </body>
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</article>