毕业论文-基于基于遗传算法的医学图像研究程序清单(终稿).doc

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