Flame Image Segmentation Based on the Bee Colony Algorithm with Characteristics of Levy Flights

Xiaolin Zhang, Tao Yang and Ningning Cui

Mathematical Problems in Engineering, 2015, vol. 2015, 1-8

Abstract:

The real-time processing of the image segmentation method with accuracy is very important in the application of the flame image detection system. This paper considers a novel method for flame image segmentation. It is the bee colony algorithm with characteristics enhancement of Levy flights against the problems of the algorithm during segmentation, including long calculation time and poor stability. By introducing the idea of Levy flights, this method designs a new local search strategy. By setting the current optimal value and based on the collaboration between the populations, it reinforces the overall convergence speed. By adopting the new fitness evaluation method and combining it with the two-dimensional entropy multithreshold segmentation principle, this paper develops a threshold segmentation test of the flame image. Test results show that this method has some advantages in terms of accuracy of threshold selection and calculation time. The robustness of the algorithm meets the actual demands in the engineering application.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2015/805075.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2015/805075.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:805075

DOI: 10.1155/2015/805075

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().