Science, Vol 248, Issue 4960, 1209-1211
Copyright © 1990 by American Association for the Advancement of Science
A two-dimensional analog VLSI circuit for detecting discontinuities in early vision
JG Harris,
C Koch,
and
J Luo
Computation and Neural Systems Program, California Institute of Technology, Pasadena 91125.
A large number of computer vision algorithms for finding intensity edges, computing motion, depth, and color, and recovering the three-dimensional shape of objects have been developed within the framework of minimizing an associated "energy" or "cost" functional. Particularly successful has been the introduction of binary variables coding for discontinuities in intensity, optical flow field, depth, and other variables, allowing image segmentation to occur in these modalities. The associated nonconvex variational functionals can be mapped onto analog, resistive networks, such that the stationary voltage distribution in the network corresponds to a minimum of the functional. The performance of an experimental analog very-large-scale integration (VLSI) circuit implementing the nonlinear resistive network for the problem of two-dimensional surface interpolation in the presence of discontinuities is demonstrated; this circuit is implemented in complementary metal oxide semiconductor technology.
