A new method for edge detection

Ying Li, Yan Ning Zhang, Rong Chun Zhao, Li Cheng Jiao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A hybrid genetic quantum algorithm (GQA) is proposed for edge detection. GQA is based on the concept and principles of quantum computing such as qubits and superposition of states. By adopting qubit chromosome, GQA can represent a linear superposition of solutions due to its probabilistic representation. Thus, GQA has a better characteristic of diversity and better global search capability than classical approaches. We combine GQA and the local search technique to the problem of edge detection. Experiment results show that the algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.

Original languageEnglish
Title of host publicationInternational Conference on Machine Learning and Cybernetics
Pages1780-1784
Number of pages5
StatePublished - 2003
Event2003 International Conference on Machine Learning and Cybernetics - Xi'an, China
Duration: 2 Nov 20035 Nov 2003

Publication series

NameInternational Conference on Machine Learning and Cybernetics
Volume3

Conference

Conference2003 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityXi'an
Period2/11/035/11/03

Keywords

  • Edge detection
  • Genetic quantum algorithm (GQA)
  • Quantum chromosome

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