asm.m

cootes提出的ASM算法的matlab实现。在cootes用于课堂使用的源代码的基础上改写。改正了原来代码中的一些错误

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Based on (unless otherwise stated):%%%
%%% Active Contour Models--Their Training & Application
%%%     T.F.Cootes, C.J.Taylor, et.al.
%%%        Computer Vision and Image Understanding,
%%%        Vol.61 No.1,January pp.38-59, 1995
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%  and for the multiresolution part:
%%% 
%%%  Active Shape Models: Evaluation of a Multi-Resolution Method
%%%  for Improving Image Search
%%%
%%%  T.F.Cootes, C.J.Taylor, A.Lanitis
%%%  Proc. British Machine Vision Conference, vol. 1 ,
%%%  1994, Ed.E.Hancock   BMVA Press.  pp327-336
%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%
%%% Programming done by:
%%% Ghassan Hamarneh
%%% Image Analysis Group
%%% CHALMERS UNIVERSITY OF TECHNOLGY
%%% Feng Xuetao
%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%Using uiwait and helpdlg
%uiwait(helpdlg({'A C T I V E     S H A P E      M O D E L S' ...
%      '        with  Multi-Resolution statistics ' ''...
%      'By ... ' '' 'Ghassan Hamarneh' '' ['done: 11-Aug-1997 -- today: ...',date] },'ASM'));

clear;
clc;


%help information
% uiwait(helpdlg({'HELP INFORMATION:',...
%       '',...
%       '  .I. This Program is divided into 3 main stages:',...
%       '        you can choose to skip any one of them',...
%       '        1 TRAINING        ',...
%       '        2 TRYING WEIGHTS  ',...
%       '        3 APPLICATION     ',...
%       '',...
%       ' .II. Follow the instructions in the dialog boxes.',...
%       '',...
%       '.III. Click Cancel in any dialog box to quit.',...
%       '',...
%    },'ASM'));
   
ButtonName=questdlg('Do you want to train?','ASM');
DidTrain=ButtonName;
if(strcmp(ButtonName,'Cancel'))
   msgbox('Terminating: cancelled request to train.','ASM');
   return; 
elseif  (strcmp(ButtonName,'Yes'))
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
   %%     TRAINING STAGE      %%
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
   
   %Number of shapes in training set = NumTrnSetImgs
   %Number of landmark points = NumLandMarkPts
   %Number of dimensions = D = 2
%   uiwait(helpdlg('THIS IS THE FIRST STAGE: TRAINING STAGE.','ASM'));   
%   uiwait(helpdlg('Now, you will enter some initialization information used for training.','ASM'));
   %Using the inputdlg
   prompt={'Enter Contours Ending Points. (Last entry is no. of landmarks, ex. [8 16 27])',...
         'Enter Percentage of explained variance (0-1):',...
         'Enter Number of points along training profile above landmark (1,2,3,...):',...
         'Enter Number of points along training profile below landmark (1,2,3,...):'};
   def={'[24 48]','0.90','5','5'};
   TheTitle='ASM';
   lineNo=[1,1,1,1];
   answer=inputdlg(prompt,TheTitle,lineNo,def,'on');
   if isempty(answer) msgbox('Terminating: cancelled inputing initialization info. for training','ASM'); return; end;
   
   ContoursEndingPoints=str2num(answer{1});
   ExplainPercent= str2num(answer{2});
   TrnPntsAbove  = str2num(answer{3});
   TrnPntsBelow  = str2num(answer{4});   
   
   NumLandMarkPts=ContoursEndingPoints(end);
   
   
   %STEP 1 -----------------
   %Obtain landmark coordinates for each shape in the training set
   %Result: 'unaligined training set shape coordinates' matrix Xu with rows=2*NumLandMarkPts & cols=NumTrnSetImgs
   
   ButtonMark=questdlg('标点?  Yes:对样本进行标点  No:读入已标点文件（前面输入的ContoursEndingPoints被取代）','ASM');
   if(strcmp(ButtonMark,'Cancel'))
      msgbox('Terminating: 训练过程中断','ASM');
      return; 
   elseif  (strcmp(ButtonMark,'Yes'))     % 对样本进行标点
      
       
       [Xu,TrnImgFiles]=GetTrnSetCoor(NumLandMarkPts,ContoursEndingPoints);
       NumTrnSetImgs=length(TrnImgFiles);
       if NumTrnSetImgs==0
            msgbox('no bmp file'); return;
       end
       if Xu==0  msgbox('Terminating: cancelled loading images','ASM'); return; end
       
   elseif (strcmp(ButtonMark,'No'))    % 读入已标点文件（前面输入的ContoursEndingPoints被取代）
      clear ContoursEndingPoints NumLandMarkPts;
      [fname,pname]=uigetfile('*.mat','读入已标点文件');
       if fname==0; msgbox('Terminating: cancelled loading data (.mat) file','ASM'); return; end
	  load([pname,fname]);
      if ~(exist('ContoursEndingPoints') & exist('NumLandMarkPts') & exist('Xu') & exist('TrnImgFiles'))
          msgbox('选择了错误的标点文件');
          return;
      end
   end
   

     

   figure
   PlotShapes(Xu,'ASM: unaligined training set',ContoursEndingPoints);
      
   %STEP 1.1 -----------------
   %Calculate the Mean Normalized Derivative Profile for each landmark point
   %RESULT: a 2D array of NumLandMarkPts Profiles
   %Calculate the covariance matrix of the Mean Normalized Derivative Profiles for each landmark
   %RESULT: a cell array of squares arrays of length (1+TrnPntsAbove+TrnPntsBelow)-1
   
   MaxNumPyramidLevels=GetMaxNumPyramidLevels(TrnImgFiles);
   
   uiwait(msgbox(['Using ',num2str(MaxNumPyramidLevels),' levels in image pyramid'],'ASM'));      
   
   [MnNrmDrvProfiles,ProfilesCov]=GetProfileStatistics(TrnImgFiles,Xu,TrnPntsAbove,TrnPntsBelow,ContoursEndingPoints,MaxNumPyramidLevels);
   
   
   %STEP 2 -----------------
   %Find the weighting matrix to give more significance to those points which tend to be stable
   %RESULT: 'landmark points weighting matrix' square matrix W with rows=cols=NumLandMarkPts
   
   uiwait(helpdlg({'Now, the weighting matrix will be calculated,'...
         'the shapes will be aligned and' ...
         'the training set statistics will be obtained.'},'ASM'));
   W=GetWeights(Xu);
   
   
   %STEP 3 -----------------
   %Align the shapes of the training set using the obtained coordinates
   %RESULT: 'aligned training set shape coordinates' matrix Xa
   
   
   Xa=AlignTrnSetCoor(Xu,W,ContoursEndingPoints);
   figure
   PlotShapes(Xa,'ASM: aligined training set',ContoursEndingPoints);
   
   
   
   %STEP 4 -----------------
   %Obtaining the statistical description of the training set shape coordinates
   %REUSLT: 'Statistical Model x=xm + P*b'  where,
   %           xm: coordinates of mean shape -> 2*NumLandMarkPts x 1
   %            P: matrix of first t eigenvectors of covariance matrix -> 2*NumLandMarkPts x t
   %            b: vector of weights -> t x 1
   
   [MeanShape,tEigenvectors,tEigenValues]=GetShapeStatistics(Xa,ExplainPercent);
      
   
   ButtonName=questdlg('Do you want to save training results','ASM');
   if(strcmp(ButtonName,'Cancel'))
      msgbox('Terminating: cancelled request to save training results','ASM');
      return; 
   elseif  (strcmp(ButtonName,'Yes'))      
      [newmatfile, newpath] = uiputfile('*.mat', 'ASM: Save as...');
      if(newmatfile==0)msgbox('Terminating: cancelled entering .mat file name for save','ASM'); return; end
      save([newpath,newmatfile],'MeanShape','tEigenvectors','tEigenValues','W','ContoursEndingPoints',...
         'MnNrmDrvProfiles','ProfilesCov','TrnPntsBelow','TrnPntsAbove','MaxNumPyramidLevels');
   end
end


if (~strcmp(DidTrain,'Yes'))  %if did not do training
   uiwait(helpdlg('Since you chose no training, you will have to load a previous data (.mat) file.','ASM'));
   [fname,pname]=uigetfile('*.mat','ASM: choose *.mat file to load');
   if fname==0; msgbox('Terminating: cancelled loading data (.mat) file','ASM'); return; end

   
   load([pname,fname])   
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%    TRY WEIGHTS          %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ButtonName=questdlg('Do you want to try weights?','ASM');
if(strcmp(ButtonName,'Cancel'))
   msgbox('Terminating: cancelled request to try weights.','ASM');
   return; 
elseif  (strcmp(ButtonName,'Yes'))
   %trying different weights b in X=M+Pb
%   uiwait(helpdlg('THIS IS THE SECOND STAGE: TRYING WEIGHTS.','ASM'));
%   uiwait(helpdlg('Now, you will enter different weight values for b in X = Xmean + P*b.','ASM'));
   TerminateNotContinue = TryWeights(MeanShape,tEigenvectors,ContoursEndingPoints);
   %TerminateNotContinue = TryWeights_XT(MeanShape,tEigenvectors,ContoursEndingPoints);
   if TerminateNotContinue msgbox('Terminating: cancelled trying weights','ASM'); return; end
end


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%    APPLICATION STAGE    %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

ButtonName=questdlg('Do you want to search for a shape in an image?','ASM');
if(strcmp(ButtonName,'Cancel'))
   msgbox('Terminating: cancelled request to search for a shape.','ASM');
   return; 
elseif  (strcmp(ButtonName,'Yes'))
%   uiwait(helpdlg('THIS IS THIRD STAGE: APPLICATION STAGE.','ASM'));
   uiwait(helpdlg('Now, you will choose an image to search and enter some initialization information','ASM'));
%   TerminateNotContinue=FindShapeInImage(MeanShape,tEigenvectors,tEigenValues,W,ContoursEndingPoints,...
%      MnNrmDrvProfiles,ProfilesCov,TrnPntsBelow,TrnPntsAbove,MaxNumPyramidLevels);
   TerminateNotContinue=iFindShapeInImage(MeanShape,tEigenvectors,tEigenValues,W,ContoursEndingPoints,...
      MnNrmDrvProfiles,ProfilesCov,TrnPntsBelow,TrnPntsAbove,2);
   
   if TerminateNotContinue msgbox('Terminating: cancelled searching image','ASM'); return; end
end

msgbox('Done!','ASM');