DocumentCode
3392729
Title
A neural network approach to represent raster images by 3-order polynomials
Author
Tsui, T.S. ; Hai-Yen Hau ; Hsieh, C.M.
Author_Institution
Dept. of Appl. Math., Chung Hsing Univ., Taichung, Taiwan
fYear
1993
fDate
29-31 Mar 1993
Firstpage
40
Lastpage
46
Abstract
Several approaches have been proposed to transform raster image into vectors. The authors propose a method which uses the characteristics of neural networks and monotonic concave functions to select the optimal windows and control points, then they use the method proposed by T. S. Tsui et. al. (1992) to transform a raster image into vectors. Experiments show that this neural network approach is robust in the presence of noise
Keywords
image processing; neural nets; polynomials; 3-order polynomials; control points; monotonic concave functions; neural network approach; optimal windows; raster images representation; CADCAM; Computer aided manufacturing; Computer applications; Computer displays; Engineering drawings; Geographic Information Systems; Neural networks; Optimal control; Permission; Polynomials;
fLanguage
English
Publisher
ieee
Conference_Titel
Developing and Managing Intelligent System Projects, 1993., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-8186-3730-7
Type
conf
DOI
10.1109/DMISP.1993.248638
Filename
248638
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