DocumentCode :
323861
Title :
Neural vision system and applications in image processing and analysis
Author :
Guan, Ling ; Perry, Stuart ; Romagnoli, Raffaele ; Wong, Hausan ; Kong, Haosong
Author_Institution :
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Volume :
2
fYear :
1998
fDate :
12-15 May 1998
Firstpage :
1245
Abstract :
We present a computer vision system based on an integrated neural network architecture. In the low level vision subsystem, a network of networks-a biologically inspired network is used to recursively perform filtering, segmentation and edge detection; in the intermediate level and the high level, hierarchically structured arrays of self-organizing tree maps-extension of the popular self-organizing map are utilized to carry out image/feature analysis. The system has been applied to solve a number of real world problems. Some interesting and encouraging results are reported
Keywords :
adaptive filters; adaptive signal processing; computer vision; edge detection; feature extraction; image segmentation; neural net architecture; recursive filters; self-organising feature maps; sonar imaging; adaptive filtering; biologically inspired network; computer vision system; edge detection; feature analysis; feature extraction; filtering; hierarchically structured arrays; image analysis; image processing; integrated neural network architecture; low level vision subsystem; network of networks; neural vision system; pattern classification; real world problems; segmentation; self-organizing tree maps; sonar image processing; Application software; Computer architecture; Computer vision; Filtering; Image analysis; Image edge detection; Image processing; Image segmentation; Machine vision; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
ISSN :
1520-6149
Print_ISBN :
0-7803-4428-6
Type :
conf
DOI :
10.1109/ICASSP.1998.675497
Filename :
675497
Link To Document :
بازگشت