Contributing Editor's Note: Retrieving digital images -
the way people look at and understand pictures - promises faster,
more accurate image database searches. The new approach considers
no information other than the image itself. Just as a person shown
a picture of a horse can extract the features characteristic of
horses and then identify other pictures that contain horses, so
does the new approach. The new system retrieves relevant images
from an image database or the web on the basis of
automatically-derived image features or content.
Abstract: The need for efficient content-based image
retrieval has increased tremendously in many application areas
such as biomedicine, military, commerce, education, and Web image
classification and searching. We present here SIMPLIcity
(Semantics-sensitive Integrated Matching for Picture LIbraries),
an image retrieval system, which uses semantics classification
methods, a wavelet-based approach for feature extraction, and
integrated region matching based upon image segmentation. As in
other region-based retrieval systems, an image is represented by a
set of regions, roughly corresponding to objects, which are
characterized by color, texture, shape, and location. The system
classifies images into semantic categories, such as
textured-nontextured, graph-photograph. Potentially, the
categorization enhances retrieval by permitting
semantically-adaptive searching methods and narrowing down the
searching range in a database. A measure for the overall
similarity between images is developed using a region-matching
scheme that integrates properties of all the regions in the
images. Compared with retrieval based on individual regions, the
overall similarity approach (1) reduces the adverse effect of
inaccurate segmentation, (2) helps to clarify the semantics of a
particular region, and (3) enables a {\it simple} querying
interface for region-based image retrieval systems. The
application of SIMPLIcity to several databases, including a
database of about 200,000 general-purpose images, has demonstrated
that our system performs significantly better and faster than
existing ones. The system is fairly robust to image
alterations.
- SIMPLIcity:
Semantics-sensitive Integrated Matching for Picture
Libraries, James
Z. Wang, Jia Li, Gio Wiederhold, IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol. 23,
2001. (to appear)
- Region-Based
Image Retrieval,
PSU Website
- Scalable
Integrated Region-Based Image Retrieval Using IRM And
Statistical
Clustering,
James Z. Wang, Yanping Du, Proc. ACM and IEEE
Joint Conference on Digital Libraries, Roanoke, VA,
ACM, June 2001.
- Integrated
Region-Based Image
Retrieval, James Z.
Wang, Kluwer Academic, Publishers, 190 pages,
2001.
- Contributed by Val
Bykoski