A simplified statistical image segmentation algorithm for the cellular neural/nonlinear networks universal machine (CNN/UM), which is a new image processing tool, is developed. It contains thousands of cells with analog dynamics, local memories and processing units. The modified metropolis dynamics (MMD) optimization method is implemented into the raw analog architecture of the CNN-UM. Within the architecture, VLSI CNN chips can execute a pseudo-stochastic relaxation algorithm of about 100 iterations in about 100 μs.
|Number of pages||17|
|Publication status||Published - Jun 1 2000|
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering