Abstract
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.
Recommended Citation
J. G. Harris et al., "A Two-dimensional Analog VLSI Circuit For Detecting Discontinuities In Early Vision," Science, vol. 248, no. 4960, pp. 1209 - 1211, American Association for the Advancement of Science, Jan 1990.
The definitive version is available at https://doi.org/10.1126/science.2349479
Department(s)
Electrical and Computer Engineering
Publication Status
Full Access
International Standard Serial Number (ISSN)
0036-8075
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 American Association for the Advancement of Science, All rights reserved.
Publication Date
01 Jan 1990
PubMed ID
2349479
