Abstract (EN):
This paper presents a novel methodology to match
contours of objects represented in images. In the matching, we
use sets of ordered points extracted from the external contours of
the objects. Each of these points defines a vertex of a polygon to
be associated to the correspondent contour. To establish the
matching, we compute a cost matching matrix by comparing the
amplitudes of the angles defined by the vertices of one of the
contours with the amplitudes of the angles defined by the vertices
of the other contour. Afterwards, the optimal global matching
that preserves the contours points orders is determined using an
optimization algorithm based on dynamic programming;
defining the optimal global matching as the one that presents the
minimum sum of the costs of all individual matches established.
Based on the matching found, we present a methodology to
compute the geometric transformation of similarity that best
aligns the contours matched. The obtained matching results were
good for contours defined by few points and the computation
time was always very low.
Language:
English
Type (Professor's evaluation):
Scientific
Contact:
www.fe.up.pt/~tavares