Boundary detection based on neural networks model

D. C.Douglas Hung, K. T. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationThird Int Conf Tools Artif Intell
PublisherPubl by IEEE
Number of pages4
ISBN (Print)0818623004
StatePublished - Jan 1 1992
EventThird International Conference on Tools for Artificial Intelligence - San Jose, CA, USA
Duration: Nov 5 1991Nov 8 1991


OtherThird International Conference on Tools for Artificial Intelligence
CitySan Jose, CA, USA

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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