DocumentCode
2628075
Title
Nonlinear analog networks for image smoothing and segmentation
Author
Lumsdaine, A. ; Wyatt, J. ; Elfadel, I.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., MIT, Cambridge, MA, USA
fYear
1990
fDate
1-3 May 1990
Firstpage
987
Abstract
Image smoothing and segmentation algorithms are frequently formulated as optimization problems. Linear and nonlinear (reciprocal) resistive networks have solutions characterized by an extremum principle. Thus, appropriately designed networks can automatically solve certain smoothing and segmentation problems in robot vision. Switched linear resistive networks and nonlinear resistive networks are considered for such tasks. Some fundamental theorems and simulation results are provided
Keywords
analogue circuits; computer vision; computerised picture processing; nonlinear network synthesis; extremum principle; image smoothing; nonlinear resistive networks; optimization problems; resistive networks; robot vision; segmentation algorithms; switched linear resistive networks; Computer science; Computer vision; Equations; Image segmentation; Laboratories; Minimization methods; Robot vision systems; Robotics and automation; Smoothing methods; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location
New Orleans, LA
Type
conf
DOI
10.1109/ISCAS.1990.112269
Filename
112269
Link To Document