Generalized skeleton formation for texture segmentation
Zs. Marczell, Zs. Kalmár and A. Lõrincz
Neural Network World
6,
79--87
(1996)
Abstract
An algorithm and an artificial neural architecture that
approximates the algorithm are proposed for the formation of
generalized skeleton transformations. The algorithm includes the
original grassfire proposal of Blum and is extended with an
integrative on-center off-surround detector system. It is shown
that the algorithm can elicit textons by skeletonization. Slight
modification of the architecture corresponds to the Laplace
transformation followed by full wave rectification, another
algorithm for texture discrimination proposed by Bergen and
Adelson.
