DocumentCode
3324653
Title
An adaptive neural net approach to the segmentation of mixed gray-level and binary pictures
Author
Troudet, Thierry ; Tabatabai, Ali
Author_Institution
Bell Commun. Res., Red Bank, NJ, USA
fYear
1988
fDate
24-27 July 1988
Firstpage
585
Abstract
An adaptive neural network architecture is proposed to perform segmentation in real time for mixed gray-level and binary pictures. In this approach the composite picture is divided into binary and image blocks based on a dichotomy measure computed by an adaptive neural net. A VLSI implementation of such a net in 2- mu m CMOS technology is described and simulated for a maximum block size of 256 pixels.<>
Keywords
CMOS integrated circuits; VLSI; computerised picture processing; neural nets; 2 micron; 256 pixel; CMOS technology; VLSI; adaptive neural network; architecture; binary pictures; computerised picture processing; dichotomy; gray-level; image blocks; neural net; segmentation; CMOS integrated circuits; Image processing; Neural networks; Very-large-scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1988., IEEE International Conference on
Conference_Location
San Diego, CA, USA
Type
conf
DOI
10.1109/ICNN.1988.23894
Filename
23894
Link To Document