Title :
Boundary detection based on neural networks model
Author :
Hung, D. C Douglas ; Chen, K.T.
Author_Institution :
Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
A new model of feedforward neural networks is proposed for solving the problem of robust boundary detection. Structurally, it is based on a circular mask which is characterized as a symmetrical neural network. By analyzing the weighted intermediate pattern, a dominant pattern is found to appear repeatedly for similar boundary orientation. Hence, a piecewise linearized edge could be detected by this approximation. Experimental results show that this new architecture can be applied to experience scaling effect by changing the mask size
Keywords :
learning systems; neural nets; pattern recognition; boundary detection; circular mask; feedforward; neural networks model; piecewise linearized edge; symmetrical neural network; weighted intermediate pattern; Humans; Image edge detection; Image segmentation; Information science; Neural networks; Pattern analysis; Robustness; Shape; Size measurement; Visual system;
Conference_Titel :
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-8186-2300-4
DOI :
10.1109/TAI.1991.167102
