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淮阴工学院大学生科技实践计划项目 第 15 页 共15 页
附 录 附录 一
灰度直方图双峰法分割源代码
clear, close all
B=imread('2.jpg'); %读入原始jpg格式图像
figure(1);
imshow(B),title('原始jpg格式图像');
I1=rgb2gray(B); %将原图像转化为灰度图象
figure(2);
imshow(I1),title('灰度格式图像');
[I1,map1]=gray2ind(I1,255); %将灰度图像转化为索引图像
figure(3), imhist(I1) %画出灰度直方图，以判断域值
I1=double(I1); %将unit8数组转化为double型数组
Z=I1 %将double型数组I1转存到Z中
[m, n]=size(Z);
for i=1:m
for j=1:n
if Z(i,j)>240 %灰度值大于域值时是白色
Z(i,j)=256;
end
end
end
figure(4) %画出分割后目标图像
image(Z),title('分割后图像');colormap(map1);
图像I图像格式转化及灰度直方图双峰法分割源代码
clear, close all
B=imread('she.jpg'); %读入原始jpg格式图像she
figure(1);
imshow(B),title('原始jpg格式图像');
I1=rgb2gray(B); %将原图像转化为灰度图象
figure(2);
imshow(I1),title('灰度格式图像');
[I1,map1]=gray2ind(I1,255); %将灰度图像转化为索引图像
figure(3), imhist(I1) %画出灰度直方图，以判断域值
I1=double(I1); %将unit8数组转化为double型数组
Z=I1 %将double型数组I1转存到Z中
[m, n]=size(Z);
for i=1:m
for j=1:n
if Z(i,j)>240 %灰度值大于域值时是白色
Z(i,j)=256;
end
end
end
figure(4) %画出分割后目标图像
image(Z),title('分割后图像');colormap(map1);
图像II图像格式转化及灰度直方图双峰法分割源代码
clear, close all
B=imread('she.jpg'); %读入原始jpg格式图像月亮
figure(1);
imshow(B),title('原始jpg格式图像');
I1=rgb2gray(B); %将原图像转化为灰度图象
figure(2);
imshow(I1),title('灰度格式图像');
[I1,map1]=gray2ind(I1,255); %将灰度图像转化为索引图像
figure(3), imhist(I1) %画出灰度直方图，以判断域值
I1=double(I1); %将unit8数组转化为double型数组
Z=I1 %将double型数组I1转存到Z中
[m, n]=size(Z);
for i=1:m
for j=1:n
if Z(i,j)>240 %灰度值大于域值时是白色
Z(i,j)=256;
end
end
end
figure(4) %画出分割后目标图像
image(Z),title('分割后图像');colormap(map1);
附录 二
Crtbp 函数源代码：（由谢菲尔德大学Andrew Chipperfield编写）
% CRTBP.m - Create an initial population%
% This function creates a binary population of given size and structure.
%
% Syntax: [Chrom Lind BaseV] = crtbp(Nind, Lind, Base)
%
% Input Parameters:
%
% Nind - Either a scalar containing the number of individuals
% in the new population or a row vector of length two
% containing the number of individuals and their length.
%
% Lind - A scalar containing the length of the individual
% chromosomes.
%
% Base - A scalar containing the base of the chromosome
% elements or a row vector containing the base(s)
% of the loci of the chromosomes.
%
% Output Parameter[来源:论文
s:
%
% Chrom - A matrix containing the random valued chromosomes
% row wise.
%
% Lind - A scalar containing the length of the chromosome.
%
% BaseV - A row vector containing the base of the
% chromosome loci.
% Author: Andrew Chipperfield
% Date: 19-Jan-94
function [Chrom, Lind, BaseV] = crtbp(Nind, Lind, Base)
nargs = nargin ;
% Check parameter consistency
if nargs >= 1, [mN, nN] = size(Nind) ; end
if nargs >= 2, [mL, nL] = size(Lind) ; end
if nargs == 3, [mB, nB] = size(Base) ; end
if nN == 2
if (nargs == 1)
Lind = Nind(2) ; Nind = Nind(1) ; BaseV = crtbase(Lind) ;
elseif (nargs == 2 & nL == 1)
BaseV = crtbase(Nind(2),Lind) ; Lind = Nind(2) ; Nind = Nind(1) ;
elseif (nargs == 2 & nL > 1)
if Lind ~= length(Lind), error('Lind and Base disagree'); end
BaseV = Lind ; Lind = Nind(2) ; Nind = Nind(1) ;
end
elseif nN == 1
if nargs == 2
if nL == 1, BaseV = crtbase(Lind) ;
else, BaseV = Lind ; Lind = nL ; end
elseif nargs == 3
if nB == 1, BaseV = crtbase(Lind,Base) ;
elseif nB ~= Lind, error('Lind and Base disagree') ;
else BaseV = Base ; end
end
else
error('Input parameters inconsistent') ;
end
% Create a structure of random chromosomes in row wise order, dimensions
% Nind by Lind. The base of each chromosomes loci is given by the value
% of the corresponding element of the row vector base.
Chrom = floor(rand(Nind,Lind).*BaseV(ones(Nind,1),:)) ;
% End of file
附录 三
Bs2rv函数源代码： （由谢菲尔德大学Andrew Chipperfield编写）
% BS2RV.m - Binary string to real vector
%
% This function decodes binary chromosomes into vectors of reals. The
% chromosomes are seen as the concatenation of binary strings of given
% length, and decoded into real numbers in a specified interval using
% either standard binary or Gray decoding.
%
% Syntax: Phen = bs2rv(Chrom,FieldD)
%
% Input parameters:
%
% Chrom - Matrix containing the chromosomes of the current
% population. Each line corresponds to one
% individual's concatenated binary string
% representation. Leftmost bits are MSb and
% rightmost are LSb.
%
% FieldD - Matrix describing the length and how to decode
% each substring in the chromosome. It has the
% following structure:
%
% [len; (num)
% lb; (num)
% ub; (num)
% code; (0=binary | 1=gray)
% scale; (0=arithmetic | 1=logarithmic)
% lbin; (0=excluded | 1=included)
% ubin]; (0=excluded | 1=included)
%
% where
% len - row vector containing the length of
% each substring in Chrom. sum(len)
% should equal the individual length.
% lb,
% ub - Lower and upper bounds for each
% variable.
% code - binary row vector indicating how each
% substring is to be decoded.
% scale - binary row vector indicating where to
% use arithmetic and/or logarithmic
% scaling.
% lbin,
% ubin - binary row vectors indicating whether
% or not to include each bound in the
% representation range
%
% Output parameter:
%
% Phen - Real matrix containing the population phenotypes.
%
% Author: Carlos Fonseca, Updated: Andrew Chipperfield
% Date: 08/06/93, Date: 26-Jan-94
function Phen = bs2rv(Chrom,FieldD)
% Identify the population size (Nind)
% and the chromosome length (Lind)
[Nind,Lind] = size(Chrom);
% Identify the number of decision variables (Nvar)
[seven,Nvar] = size(FieldD);
if seven ~= 7
error('FieldD must have 7 rows.');
end
% Get substring properties
len = FieldD(1,:);
lb = FieldD(2,:);
ub = FieldD(3,:);
code = ~(~FieldD(4,:));
scale = ~(~FieldD(5,:));
lin = ~(~FieldD(6,:));
uin = ~(~FieldD(7,:));
% Check substring properties for consistency
if sum(len) ~= Lind,
error('Data in FieldD must agree with chromosome length');
end
if ~all(lb(scale).*ub(scale)>0)
error('Log-scaled variables must not include 0 in their range');
end
% Decode chromosomes
Phen = zeros(Nind,Nvar);
lf = cumsum(len);
li = cumsum([1 len]);
Prec = .5 .^ len;
logsgn = sign(lb[来源:论文
(scale));
lb(scale) = log( abs(lb(scale)) );
ub(scale) = log( abs(ub(scale)) );
delta = ub - lb;
Prec = .5 .^ len;
num = (~lin) .* Prec;
den = (lin + uin - 1) .* Prec;
for i = 1:Nvar,
idx = li(i):lf(i);
if code(i) % Gray decoding
Chrom(:,idx)=rem(cumsum(Chrom(:,idx)')',2);
end
Phen(:,i) = Chrom(:,idx) * [ (.5).^(1:len(i))' ];
Phen(:,i) = lb(i) + delta(i) * (Phen(:,i) + num(i)) ./ (1 - den(i));
end
expand = ones(Nind,1);
if any(scale)
Phen(:,scale) = logsgn(expand,:) .* exp(Phen(:,scale));
end
附录 四
适应度函数target源代码：
function f=target(T,M) %适应度函数,T为待处理图像,M为域值序列
[U, V]=size(T);
W=, , length(M);
f=zeros(W,1);
for k=1:W
I=0;s1=0;J=0;s2=0; %统计目标图像和背景图像的像素数及像素之和
for i=1:U
for j=1:V
if T(i,j)<=M(k)
s1=s1+T(i,j);I=I+1;
end
if T(i,j)>M(k)
s2=s2+T(i,j);J=J+1;
end
end
end
if I==0, p1=0; else p1=s1/I; end
if J==0, p2=0; else p2=s2/J; end
f(k)=I*J*(p1-p2)*(p1-p2)/(256*256);
end
附录 五
选择函数Select源代码：（由谢菲尔德大学Hartmut Pohlheim编写）
% SELECT.M (universal SELECTion)
%
% This function performs universal selection. The function handles
% multiple populations and calls the low level selection function
% for the actual selection process.
%
% Syntax: SelCh = select(SEL_F, Chrom, FitnV, GGAP, SUBPOP)
%
% Input parameters:
% SEL_F - Name of the selection function
% Chrom - Matrix containing the individuals (parents) of the current
% population. Each row corresponds to one individual.
% FitnV - Column vector containing the fitness values of the
% individuals in the population.
% GGAP - (optional) Rate of individuals to be selected
% if omitted 1.0 is assumed
% SUBPOP - (optional) Number of subpopulations
% if omitted 1 subpopulation is assumed
%
% Output parameters:
% SelCh - Matrix containing the selected individuals.
% Author: Hartmut Pohlheim
% History: 10.03.94 file created
function SelCh = select(SEL_F, Chrom, FitnV, GGAP, SUBPOP);
% Check parameter consistency
if nargin < 3, error('Not enough input parameter'); end
% Identify the population size (Nind)
[NindCh,Nvar] = size(Chrom);
[NindF,VarF] = size(FitnV);
if NindCh ~= NindF, error('Chrom and FitnV disagree'); end
if VarF ~= 1, error('FitnV must be a column vector'); end
if nargin < 5, SUBPOP = 1; end
if nargin > 4,
if isempty(SUBPOP), SUBPOP = 1;
elseif isnan(SUBPOP), SUBPOP = 1;
elseif length(SUBPOP) ~= 1, error('SUBPOP must be a scalar'); end
end
if (NindCh/SUBPOP) ~= fix(NindCh/SUBPOP), error('Chrom and SUBPOP disagree'); end
Nind = NindCh/SUBPOP; % Compute number of individuals per subpopulation
if nargin < 4, GGAP = 1; end
if nargin > 3,
if isempty(GGAP), GGAP = 1;
elseif isnan(GGAP), GGAP = 1;
elseif length(GGAP) ~= 1, error('GGAP must be a scalar');
elseif (GGAP < 0), error('GGAP must be a scalar bigger than 0'); end
end
% Compute number of new individuals (to select)
NSel=max(floor(Nind*GGAP+.5),2);
% Select individuals from population
SelCh = [];
for irun = 1:SUBPOP,
FitnVSub = FitnV((irun-1)*Nind+1:irun*Nind);
ChrIx=feval(SEL_F, FitnVSub, NSel)+(irun-1)*Nind;
SelCh=[SelCh; Chrom(ChrIx,:)];
end
% End of function
附录 六
交叉函数recombin的源代码：（由谢菲尔德大学Hartmut Pohlheim编写）
% RECOMBIN.M (RECOMBINation high-level function)
%
% This function performs recombination between pairs of individuals
% and returns the new individuals after mating. The function handles
% multiple populations and calls the low-level recombination function
% for the actual recombination process.
%
% Syntax: NewChrom = recombin(REC_F, OldChrom, RecOpt, SUBPOP)
%
% Input parameters:
% REC_F - String containing the name of the recombination or
% crossover function
% Chrom - Matrix containing the chromosomes of the old
% population. Each line corresponds to one individual
% RecOpt - (optional) Scalar containing the probability of
% recombination/crossover occurring between pairs
% of individuals.
% if omitted or NaN, 1 is assumed
% SUBPOP - (optional) Number of subpopulations
% if omitted or NaN, 1 subpopulation is assumed
%
% Output parameter:
% NewChrom - Matrix containing the chromosomes of the population
% after recombination in the same format as OldChrom.
% Author: Hartmut Pohlheim
% History: 18.03.94 file created
function NewChrom = recombin(REC_F, Chrom, RecOpt, SUBPOP);
% Check parameter consistency
if nargin < 2, error('Not enough input parameter'); end
% Identify the population size (Nind)
[Nind,Nvar] = size(Chrom);
if nargin < 4, SUBPOP = 1; end
if nargin > 3,
if isempty(SUBPOP), SUBPOP = 1;
elseif isnan(SUBPOP), SUBPOP = 1;
elseif length(SUBPOP) ~= 1, error('SUBPOP must be a scalar'); end
end
if (Nind/SUBPOP) ~= fix(Nind/SUBPOP), error('Chrom and SUBPOP disagree'); end
Nind = Nind/SUBPOP; % Compute number of individuals per subpopulation
if nargin < 3, RecOpt = 0.7; end
if nargin > 2,
if isempty(RecOpt), RecOpt = 0.7;
elseif isnan(RecOpt), RecOpt = 0.7;
elseif length(RecOpt) ~= 1, error('RecOpt must be a scalar');
elseif (RecOpt < 0 | RecOpt > 1), error('RecOpt must be a scalar in [0, 1]'); end
end
% Select individuals of one subpopulation and call low level function
NewChrom = [];
for irun = 1:SUBPOP,
ChromSub = Chrom((irun-1)*Nind+1:irun*Nind,:);
NewChromSub = feval(REC_F, ChromSub, RecOpt);
NewChrom=[NewChrom; NewChromSub];
end
% End of function
附录 七
变异函数mut源代码 ：（由谢菲尔德大学Andrew Chipperfield编写）
% MUT.m
%
% This function takes the representation of the current population,
% mutates each element with given probability and returns the resulting
% population.
%
% Syntax: NewChrom = mut(OldChrom,Pm,BaseV)
%
% Input parameters:
%
% OldChrom - A matrix containing the chromosomes of the
% current population. Each row corresponds to
% an individuals string representation.
%
% Pm - Mutation probability (scalar). Default value
% of Pm
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