Fuzzy set methods have been used to model and manage uncertainty in
various aspects of image processing, pattern recognition and computer
vision. High-level computer vision applications hold a great potential
for fuzzy set theory because of its links to natural language.
Linguistic scene description, a language-based interpretation of
regions and their relationships, is one such application that is
starting to bear the fruits of fuzzy set theoretic involvement. In this
paper, we are expanding on two earlier endeavors. We introduce new
families of fuzzy directional relations that rely on the computation of
histograms of forces. These families preserve important relative
position properties. They provide inputs to a fuzzy rule base that
produces logical linguistic descriptions along with assessments as to
the validity of the descriptions. Each linguistic output uses hedges
from a dictionary of about thirty adverbs and other terms that can be
tailored to individual users. Excellent results from several synthetic
and real image examples show the applicability of this approach.