Two models of object perception are compared: recognition by component
s (RBC), proposed by Biederman, and structural information theory (SIT
), initially proposed by Leeuwenberg. According to RBC a complex objec
t is decomposed into predefined elementary objects, called geons. Acco
rding to SIT, the decomposition is guided by regularities in the objec
t. It is assumed that the simplest of all possible interpretations of
any object is perceptually preferred. The comparison deals with two as
pects of the models. One is the representation of simple objects-vario
us defintions of object axes are considered. It is shown that the more
these definitions account for object regularity and thus the more the
y agree with SIT, the better the object representations predict object
classification. Another topic concerns assumptions underlying the mod
els: the identification of geons is mediated by cues which are suppose
d to be invariant under varying viewpoints of objects. It is argued th
at such cues are not based on this invariance but on the regularity of
actual objects. The latter conclusion is in line with SIT. An advanta
ge of RBC, however, is that it deals with the perceptual process from
stimulus to interpretation, whereas SIT merely concerns the outcome of
the process, not the process itself.