DocumentCode
3163398
Title
Finding arrows in utility maps using a neural network
Author
den Hartog, J.E. ; ten Kate, T.K.
Author_Institution
TNO Inst. of Appl. Phys., Delft
Volume
2
fYear
1994
fDate
9-13 Oct 1994
Firstpage
190
Abstract
In this paper a new technique is proposed for the reliable classification of poor quality arrows in hand drawn utility maps. The classification uses a neural network which is trained to distinguish arrows from other line symbols. A line symbol is represented by a feature vector based on the pseudo-Euclidean distances along the skeleton. The classification is evaluated with an independent test set
Keywords
neural nets; hand drawn utility maps; line symbol; neural network; poor quality arrows; pseudo-Euclidean distances; reliable classification; Computer applications; Computer graphics; Computer networks; Intelligent networks; Neural networks; Physics; Pixel; Shape; Skeleton; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
Conference_Location
Jerusalem
Print_ISBN
0-8186-6270-0
Type
conf
DOI
10.1109/ICPR.1994.576902
Filename
576902
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