基于改进布谷鸟算法的火焰图像阈值分割算法

张晓琳; 张冲; 杨涛

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基于改进布谷鸟算法的火焰图像阈值分割算法

更新时间：2026-09-04

- 基于改进布谷鸟算法的火焰图像阈值分割算法
- Threshold Segmentation Algorithm of Flame Image Based on Modified Cuckoo Search Algorithm
- 微电子学与计算机 2017年34卷第1期页码：66-70
- 作者机构：
  
  内蒙古科技大学机构信息工程学院,内蒙古,包头,014010
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目 61164018
- DOI：
  中图分类号：
- 纸质出版：2017
- 稿件说明：
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张晓琳, 张冲, 杨涛. 基于改进布谷鸟算法的火焰图像阈值分割算法[J]. 微电子学与计算机, 2017, 34(1): 66-70.

ZHANG Xiao-lin, ZHANG Chong, YANG Tao. Threshold Segmentation Algorithm of Flame Image Based on Modified Cuckoo Search Algorithm[J]. 2017, 34(1): 66-70.
张晓琳, 张冲, 杨涛. 基于改进布谷鸟算法的火焰图像阈值分割算法[J]. 微电子学与计算机, 2017, 34(1): 66-70. DOI：

ZHANG Xiao-lin, ZHANG Chong, YANG Tao. Threshold Segmentation Algorithm of Flame Image Based on Modified Cuckoo Search Algorithm[J]. 2017, 34(1): 66-70. DOI：

摘要

提出了改进的布谷鸟算法.在改进算法中

首先利用混沌理论进行种群的初始化

提高了种群的多样性.然后自适应选择利用莱维随机游走或者改进的蛙跳算法局部搜索方式更新新的解

提高了算法的局部搜索能力和算法的收敛速度.与其他算法相比较

改进算法显示了其强大的优化精度和高速度性

提高了图像的分割效率.

Abstract

To improve the performance of the algorithm

an modified cook search algorithm is proposed. In the modified algorithm

first chaos theory is utilized to enhance the variety of the initial population. Then

Levy random walk or modifieds shuffed frog leaping algorithm local search is adaptively chosen to update the new solution

improving the local search ability and convergence rate of the algorithm. Comparison results with other algorithms indicate that the modified algorithm displays strong optimizing accuracy and high speed

improving the segmentation efficiency of the algorithm.

关键词

Keywords

references

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王李进, 伊义龙, 钟一文. 逐维改进的布谷鸟搜索算法[J]. 软件学报. 2013, 24(11): 2687-2698. DOI: 2687

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