MultimodalBiometricSystem/pso_total.m at master · palakanmol31/MultimodalBiometricSystem · GitHub

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function pso_total
clc;
diary Status_pso.txt
pathname1= 'F:\combined\Testing';
best_rule=dlmread('best_optimal_value.txt');
pFAR =dlmread('pFAR.txt');
pFRR =dlmread('pFRR.txt');
fFAR =dlmread('fFAR.txt');
fFRR=dlmread('fFRR.txt');
for e=1:20
    for f=4:5
        pathname=strcat(pathname1,'\Group',num2str(e),'_',num2str(f),'\')
        filename=dir(pathname);
        filename_size=size(filename,1);
        for i=3:filename_size
            [path name ext]=fileparts(filename(i).name);

            if strcmp(ext,'.txt')==1
                if strcmp(name(1),'t')==1
                    p_test=dlmread(strcat(pathname,'\',name,ext)) ;
                elseif strcmp(name(1),'f')==1
                    f_test=dlmread(strcat(pathname,'\',name,ext));
                elseif strcmp(name(1),'s')==1
                    match_mat=dlmread(strcat(pathname,'\',name,ext));
                end
            else
                continue ;
            end

        end
        train_pathname='F:\combined\Training';
        p=0;
        for l=1:20
            for k=1:3
                p=p+1;
                t_path=strcat(train_pathname,'\Group',int2str(l),'_',int2str(k));
                filename=dir(t_path);
                filename_size=size(filename,1);
                for i=3:filename_size
                    [path name ext]=fileparts(filename(i).name);
                    if strcmp(ext,'.txt')==1
                        if strcmp(name(1),'t')==1
                            p_train=dlmread(strcat(t_path,'\',name,ext));
                        elseif strcmp(name(1),'f')==1
                            f_train=dlmread(strcat(t_path,'\',name,ext));
                        end
                    else
                        continue ;
                    end
                end
                finger_score(p)=match_mat(p);

                palmprint_score(p)=p_mat(p_train,p_test);


            end
        end
        j=1;
        for i=1:20
            p_score(i)=(palmprint_score(j)+palmprint_score(j+1)+palmprint_score(j+2))/3 ;
            f_score(i)=(finger_score(j)+finger_score(j+1)+finger_score(j+2))/3 ;

            j=j+3;
        end


        [p_1 p_user]=max(p_score);
        if p_user==e
            s0=1;
        else
            s0=0;
        end
        [f_1 f_user]=max(f_score);
        if f_user==e
            s1=1;
        else
            s1=0;
        end
        answer=[];
        for x=1:16
            val(x,1)=s0*log10((1-pFRR(best_rule(x,6)))/pFAR(best_rule(x,6)))+(1-s0)*log10(pFRR(best_rule(x,6))/1-pFAR(best_rule(x,6)))+s1*log10((1-fFRR(best_rule(x,6)))/fFAR(best_rule(x,6)))+(1-s1)*log10(fFRR(best_rule(x,6))/1-fFAR(best_rule(x,6)));
            threshold(x,1) = log10(best_rule(x,2)/2-best_rule(x,2));
            if(val(x,1)>threshold(x,1))
                answer=[answer x];
            end
        end
        if isempty(answer)
            display('User is imposter');
        else
            display('User is genuine with fusion rules and optimum values as : ');
            display('     RULE       ERROR       CFA      FAR       FRR')
            for q=1:size(answer,2)
                a(q,:)=[answer(q)  best_rule(answer(q),1)  best_rule(answer(q),2)  best_rule(answer(q),3)  best_rule(answer(q),5) ];
            end
            display(a);

        end
    end
end
%fclose(fid);
diary off
end