Clustering and Symbolic Signature Classification for Image Retrieval
by
Jenny Yuen
When we look around, we categorize objects in an unconscious level. We can
tell there is a house, a building, or the sky. But the conceptualization of
an object as a house, a building, or the sky depends on various factors.
There can be many different types of houses, depending on the geographical
zone. A skyscraper is a building but an old medieval castle is, too. The sky
is different on a rainy day compared to a sunny one, or at night. If we are
talking about images with objects, an object can be different from others in
size and view point, the object can be partially occluded by another, or the
image might only capture a part of the object. Therefore, these barriers of
ambiguity and diversity are obstacles to finding an easy solution for
automated recognitions of objects in images. The purpose of this research is
to automate object recognition of a finite set of known categories by
analyzing features like color, texture, and structure in an image and
introducing symbolic signatures in the representation of objects found in an
image.
Advised by Linda Shapiro
MGH 251
Wednesday
February 4, 2004
3:30 - 4:20 pm