DocumentCode
319634
Title
Neural network based image recognition system using geometrical moment
Author
Chung, Yuk Ying ; Wong, Man To
Author_Institution
Space Centre for Satellite Navigation, Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume
1
fYear
1997
fDate
4-4 Dec. 1997
Firstpage
383
Abstract
Geometrical moments (GM) have been used in the classification of four closed planar shapes (Gupta and Srinath, 1987). Also a neural network approach for the classification of four closed planar shapes has been used in Khotanzad and Lu (1990). In this paper, a backpropagation neural network is used in the recognition of six different kinds of hand tools using geometrical moments. Experimental results indicate that the neural network approach gives a better recognition accuracy when compared with the two conventional statistical classifiers-namely the single nearest neighbour and minimum-mean-distance. Recognition accuracy using a neural network is over 98%.
Keywords
backpropagation; feature extraction; hand tools; image classification; neural nets; backpropagation neural network; geometrical moment; hand tools; minimum-mean-distance method; neural network based image recognition system; recognition accuracy; single nearest neighbour method; statistical classifiers; Australia; Backpropagation; Dynamic range; Image recognition; Image storage; Neural networks; Satellite navigation systems; Shape; Space technology; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE
Conference_Location
Brisbane, Qld., Australia
Print_ISBN
0-7803-4365-4
Type
conf
DOI
10.1109/TENCON.1997.647336
Filename
647336
Link To Document