Yy. Cai et al., QUALITATIVE PRIMITIVE IDENTIFICATION USING FUZZY CLUSTERING AND INVARIANT APPROACH, Image and vision computing, 14(7), 1996, pp. 451-464
Citations number
30
Categorie Soggetti
Computer Sciences, Special Topics",Optics,"Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence","Computer Science Software Graphycs Programming","Computer Science Theory & Methods
This paper addresses the issue of qualitative primitive extraction fro
m range images. The fuzzy C-shell clustering technique is applied to p
artition range images into a set of quadric shells. Once the best-fitt
ing quadric shells have been recovered, five types of invariants are u
sed to classify the qualitative shapes and represent the geometric par
ameters of the shapes. Finally, the extracted quadric shells are local
ised in terms of quadric centre(s), quadric directions, and any axes o
f revolution. Using fuzzy shell clustering, the shell features can be
segmented and fitted simultaneously, and individual best-fitted shells
can be clustered concurrently. The integration of the partition with
the invariant analysis makes it possible to identify qualitative featu
res from depth maps.