  Object categorization is a hot issue of an image mining. Contextual
information between objects is one of the important semantic knowledge of an
image. However, the previous researches for an object categorization have not
made full use of the contextual information, especially the spatial relations
between objects. In addition, the object categorization methods, which
generally use the probabilistic graphical models to implement the incorporation
of contextual information with appearance of objects, are almost inevitable to
evaluate the intractable partition function for normalization. In this work, we
introduced fully-connected fuzzy spatial relations including directional,
distance and topological relations between object regions, so the spatial
relational information could be fully utilized. Then, the spatial relations
were considered as well as co-occurrence and appearance of objects by using
energy-based model, where the energy function was defined as the region-object
association potential and the configuration potential of objects. Minimizing
the energy function of whole image arrangement, we obtained the optimal label
set about the image regions and addressed the evaluation of intractable
partition function in conditional random fields. Experimental results show the
validity and reliability of this proposed method.
