SIMPLIcity: Semantics-sensitive Integrated Matching
for Picture LIbraries
James Z. Wang, Jia Li, Gio Wiederhold
Stanford University, Stanford, CA 94305
We present here SIMPLIcity (Semantics-sensitive Integrated Matching
for Picture LIbraries), an image retrieval system using semantics
classification and integrated region matching (IRM) based upon image
segmentation. The SIMPLIcity system represents an image by a set of
regions, roughly corresponding to objects, which are characterized by
color, texture, shape, and location. The system classifies images
into categories which are intended to distinguish semantically
meaningful differences, such as textured versus nontextured, indoor
versus outdoor, and graph versus photograph. Retrieval is enhanced by
narrowing down the searching range in a database to a particular
category and exploiting semantically-adaptive searching methods. A
measure for the overall similarity between images, the IRM distance,
is defined by a region-matching scheme that integrates properties of
all the regions in the images. This overall similarity approach
reduces the adverse effect of inaccurate segmentation, helps to
clarify the semantics of a particular region, and enables a simple
querying interface for region-based image retrieval systems. The
application of SIMPLIcity to a database of about 200,000
general-purpose images demonstrates accurate retrieval at high speed.
The system is also robust to image alterations.
Full Paper in Color
Copyright 2000 Springer-Verlag.
Personal use of this
material is permitted. However, permission to reprint/republish this
material for advertising or promotional purposes or for creating new
collective works for resale or redistribution to servers or lists, or
to reuse any copyrighted component of this work in other works, must
be obtained from the Springer-Verlag.
July 10 2000