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Cluster Computing

, Volume 22, Supplement 2, pp 3505–3512 | Cite as

Analysis of image processing algorithm based on bionic intelligent optimization

  • Yuetao DuEmail author
  • Nana Yang
Article

Abstract

In order to improve the speed and the accuracy of image segmentation, the nectar source fitness and defect nectar source replacement are improved through original artificial bee colony algorithm, in this paper, an optimized algorithm for combined use of artificial bee colony and Ostu is proposed. This method simulates the process of honey bee colony, and the threshold is regarded as nectar source, the fitness is regarded as the content of nectar source, then the segmentation of the image is completed successfully. In order to improve the speed of image segmentation, the long-term use of honey in original artificial bee colony is replaced with new nectar source, which can improve the running speed of the algorithm; In order to increase the accuracy of the algorithm and avoid local optimization, the fitness formula is meticulous through the fitness adjustment on nectar source. The experimental results show that the image segmentation reaches the ideal state, and the speed and precision of the segmentation are improved.

Keywords

Artificial bee colony algorithm Optimization Nectar source fitness Defect nectar source replacement 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Electronic Information EngineeringXi’an Technological UniversityXi’anChina
  2. 2.School of Art and MediaXi’an Technological UniversityXi’anChina

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