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
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;
Conference_Titel :
Developing and Managing Intelligent System Projects, 1993., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-3730-7
DOI :
10.1109/DMISP.1993.248638
