Sufficient conditions for 1-D CNNs with opposite-sign templates to perform connected component detection

Norikazu Takahashi, Ken Ishitobi, Tetsuo Nishi

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Connected component detection (CCD) is an important image processing task done by one-dimensional cellular neural networks (1-D CNNs). Recently, some sufficient conditions for 1-D CNNs with the antisymmetric template A = [s, p, - s] to perform CCD have been derived under the assumption that the outputs of the boundary cells are set to 1 or -1. In this paper, we extend these results to 1-D CNNs with the opposite-sign template A = [r, p, - s]. It is shown that the 1-D CNN can perform CCD for a wide range of parameter space. Therefore we can design 1-D CNNs which not only can perform CCD but also are robust against small perturbations of the parameters.

Original languageEnglish
Article number4253349
Pages (from-to)3159-3162
Number of pages4
JournalProceedings - IEEE International Symposium on Circuits and Systems
DOIs
Publication statusPublished - Jan 1 2007
Externally publishedYes
Event2007 IEEE International Symposium on Circuits and Systems, ISCAS 2007 - New Orleans, LA, United States
Duration: May 27 2007May 30 2007

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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