A force field driven SOM for boundary detection

Yu He, Songhua Xu, Willard L. Miranker

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

1 Scopus citations

Abstract

We will introduce a method to extract object boundaries from an image. This method utilizes a deformable curve based on the Self Organizing Map algorithm. The proposed SOM has some unique properties such as batch update and neuron insertion/deletion. These properties can make the SOM converge to object concavities as well as maintain a uniform distribution of neurons along the SOM. In comparison with other traditional active contour methods, this algorithm is less sensitive to initialization more flexible in noisy conditions. It outperforms the Gradient Vector Flow method.

Original languageEnglish (US)
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOIs
StatePublished - Dec 1 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain
Duration: Jul 18 2010Jul 23 2010

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CountrySpain
CityBarcelona
Period7/18/107/23/10

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Keywords

  • Active Contour
  • Edge Detection
  • Self Organizing Map

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