【图像分割】基于花朵授粉算法实现图像的自适应多阈值快速分割附matlab代码

1 内容介绍

为快速准确地将图像中目标和背景分离开来,将新型群体智能模型中的花朵授粉算法、最大类间阈值相结合,提出了一种图像分割新方法.该方法将图像阈值看成花朵授粉算法群算法中的花粉，利用信息熵和最大熵原理设计花朵授粉算法的适应度函数,逐代逼近最佳阈值.并利用Matlab实现了图像分割算法,对分割的结果进行分析.实验结果表明,该方法在阈值分割图像时,花朵授粉算法能够快速准确地将图像目标分离出来,分离出来的目标更加适合后序的分析和处理.

2 部分代码

% --------------------------------------------------------------------%

% Flower pollenation algorithm (FPA), or flower algorithm %

% Programmed by Xin-She Yang @ May 2012 %

% --------------------------------------------------------------------%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Notes: This demo program contains the very basic components of %

% the flower pollination algorithm (FPA), or flower algorithm (FA), %

% for single objective optimization. It usually works well for %

% unconstrained functions only. For functions/problems with %

% limits/bounds and constraints, constraint-handling techniques %

% should be implemented to deal with constrained problems properly. %

% %

% Citation details: %

%1)Xin-She Yang, Flower pollination algorithm for global optimization,%

% Unconventional Computation and Natural Computation, %

% Lecture Notes in Computer Science, Vol. 7445, pp. 240-249 (2012). %

%2)X. S. Yang, M. Karamanoglu, X. S. He, Multi-objective flower %

% algorithm for optimization, Procedia in Computer Science, %

% vol. 18, pp. 861-868 (2013). %

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

clc

clear all

close all

n=30; % Population size, typically 10 to 25

p=0.8; % probabibility switch

% Iteration parameters

N_iter=3000; % Total number of iterations

fitnessMSE = ones(1,N_iter);

% % Dimension of the search variables Example 1

d=2;

Lb = -1*ones(1,d);

Ub = 1*ones(1,d);

% % Dimension of the search variables Example 2

% d=3;

% Lb = [-2 -1 -1];

% Ub = [2 1 1];

%

% % Dimension of the search variables Example 3

% d=3;

% Lb = [-1 -1 -1];

% Ub = [1 1 1];

%

%

% % % Dimension of the search variables Example 4

% d=9;

% Lb = -1.5*ones(1,d);

% Ub = 1.5*ones(1,d);

% Initialize the population/solutions

for i=1:n,

Sol(i,:)=Lb+(Ub-Lb).*rand(1,d);

% To simulate the filters use fitnessX() functions in the next line

Fitness(i)=fitness(Sol(i,:));

end

% Find the current best

[fmin,I]=min(Fitness);

best=Sol(I,:);

S=Sol;

% Start the iterations -- Flower Algorithm

for t=1:N_iter,

% Loop over all bats/solutions

for i=1:n,

% Pollens are carried by insects and thus can move in

% large scale, large distance.

% This L should replace by Levy flights

% Formula: x_i^{t+1}=x_i^t+ L (x_i^t-gbest)

if rand>p,

%% L=rand;

L=Levy(d);

dS=L.*(Sol(i,:)-best);

S(i,:)=Sol(i,:)+dS;

% Check if the simple limits/bounds are OK

S(i,:)=simplebounds(S(i,:),Lb,Ub);

% If not, then local pollenation of neighbor flowers

else

epsilon=rand;

% Find random flowers in the neighbourhood

JK=randperm(n);

% As they are random, the first two entries also random

% If the flower are the same or similar species, then

% they can be pollenated, otherwise, no action.

% Formula: x_i^{t+1}+epsilon*(x_j^t-x_k^t)

S(i,:)=S(i,:)+epsilon*(Sol(JK(1),:)-Sol(JK(2),:));

% Check if the simple limits/bounds are OK

S(i,:)=simplebounds(S(i,:),Lb,Ub);

end

% Evaluate new solutions

% To simulate the filters use fitnessX() functions in the next

% line

Fnew=fitness(S(i,:));

% If fitness improves (better solutions found), update then

if (Fnew<=Fitness(i)),

Sol(i,:)=S(i,:);

Fitness(i)=Fnew;

end

% Update the current global best

if Fnew<=fmin,

best=S(i,:) ;

fmin=Fnew ;

end

end

% Display results every 100 iterations

if round(t/100)==t/100,

best

fmin

end

fitnessMSE(t) = fmin;

end

%figure, plot(1:N_iter,fitnessMSE);

% Output/display

disp(['Total number of evaluations: ',num2str(N_iter*n)]);

disp(['Best solution=',num2str(best),' fmin=',num2str(fmin)]);

figure(1)

plot( fitnessMSE)

xlabel('Iteration');

ylabel('Best score obtained so far');

3 运行结果

4 参考文献

[1]李小琦. 基于Matlab的图像阈值分割算法研究[J]. 软件导刊, 2014, 13(12):3.

[2]霍凤财等. "基于人工蜂群算法的图像阈值分割." 自动化技术与应用 035.002(2016):112-116.

部分理论引用网络文献，若有侵权联系博主删除。