2009 IEEE International Conference on
Systems, Man, and Cybernetics |
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Abstract
Relative position of object description are widely
used in event understanding and computer vision tasks especially
in object recognition. Use of low level features cannot give satisfactory
results when high level concepts is not easily expressible
in low level contents. Mostly researchers are concentrating on
spatio- temporal relationship between objects or regions of an
object in images. Object retrieval which is taken into account the
relative position of objects in images become important. In such
a case classical Allen relations are used. Searched object can take
various shapes and scale according to shooting. Fuzzy methods
have the ability to compensate the imprecise informations and
vagueness.
In this paper fuzzy histograms of Allen relations are used for
object retrieval. Fuzzy histograms of Allen relations are the
quantitative representation of relative object position. For this
purpose Matsakis¡¯s [9] algorithm for fuzzification of line segments
is refined. This representation is affine invariant. Query is made
by example and only corresponding relative relation between
objects is considered. Results are analyzed by a well known
Receiver Operating Characteristic curve ( ROC )method.