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

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.

Original languageEnglish (US)
Title of host publicationThird Int Conf Tools Artif Intell
PublisherPubl by IEEE
Pages254-257
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

Other

OtherThird International Conference on Tools for Artificial Intelligence
CitySan Jose, CA, USA
Period11/5/9111/8/91

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Fingerprint Dive into the research topics of 'Boundary detection based on neural networks model'. Together they form a unique fingerprint.

Cite this