Ekstraksi Ciri Tekstur Menggunakan Gray Level Co-occurrence Matrix (GLCM) Untuk Membedakan Daging Babi, Daging Kambing, dan Daging Sapi

Akhir-akhir ini sering muncul kasus di masyarakat tentang keamanan daging sapi dan kambing seperti pemalsuan daging sapi, daging kambing dipalsukan dengan daging babi oleh oknum-oknum tidak bertanggung jawab. Kondisi ini tentu saja dapat merugikan konsumen terutama konsumen di pasar tradisional dan mengingat banyaknya konsumen di kalangan masyarakat indonesia ini sebagian besar merupakan masyarakat muslim. Kurangnya pengetahuan masyarakat tentang cara membedakan daging sapi, daging kambing dengan daging babi menjadikan konsumen tidak teliti dalam membeli daging. Maka dari itu demi melindungi konsumen dari kasus penipuan seperti ini, perlu adanya suatu alat atau sistem yang dapat membantu masyarakat untuk mengenali daging sapi, daging kambing dan daging babi. Teknologi pengenalan pola saat ini telah banyak mengalami perkembangan. Hal ini dapat dimanfaatkan untuk membantu menyelesaikan masalah ini dengan membuat suatu sistem yang dapat mengklasifikasi jenis daging secara otomatis untuk mengurangi masalah-masalah tentang pemalsuan daging.

Berikut ini merupakan contoh pemrograman matlab untuk melakukan ekstraksi ciri citra daging babi, daging kambing, dan daging sapi menggunakan tekstur GLCM. Langkah-langkahnya sebagai berikut:

1. Membaca citra RGB.

Citra Asli atau Citra RGB

 

2. Memotong Citra menjadi ukuran 2091.5 x 1371.5 x 978 x 852.

 Cropping Citra


3. Resize ukuran citra yang telah di potong dengan ukuran piksel menjadi 256 x 256, agar piksel dari semua citra sama

 Resize Citra


4. Mengkonversi Citra menjadi citra keabuan yang bertujuan untuk menuju tahap selanjutnya yaitu GLCM, karena GLCM hanya dapat diolah ketika citra sudah dalam bentuk citra keabuan.

 Citra Grayscale


5. Mencari Nilai Gray-Level Co-Occurrence Matrix (GLCM), Ciri GLCM yang diekstrak adalah Angular Second Moments, Contrast, Correlation, Variance, Inverse  Different Moment, dan Entropy.

GLCM


Source code yang digunakan adalah sebagai berikut: 

seluruh citra daging dapat didownload melalui:

https://mega.nz/folder/PqYynKZQ#_XI31flX_gNlKdlE0JoaSw

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function CiriOrdeDua(Citra)
clc, clear all, warning off all; tic;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%                              Read Image                                %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[fname,pname] = uigetfile({'*.jpg';'*.bmp';'*.png';'*.tif';'*.ppm';},'Open Image');
gambar = imread([pname fname]);
figure (1);
imwrite(gambar, 'Gambar Asli.jpg');
imshow(gambar); 
title('Gambar Asli');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%                          Cropping Gambar                               %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
crop = imcrop(gambar,[2091.5 1371.5 978 852]);
figure (2); 
imwrite(crop, 'Cropping Gambar.jpg');
imshow(crop); 
title('Cropping Gambar');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%                           Resize Gambar                                %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
resize = imresize (crop,[256 256]);
figure (3);
imwrite(resize, 'Resize Citra.jpg');
imshow(resize); 
title('Resize Citra');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%                          Grayscale Gambar                              %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
grayscale = rgb2gray(resize); %proses Grayscaling
figure (4);
imwrite(grayscale, 'Citra Keabuan.jpg');
imshow(grayscale); 
title('Citra Keabuan');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%                              GLCM                                      %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Citra=grayscale;

mk000=ko000(Citra);
mk045=ko045(Citra);
mk090=ko090(Citra);
mk135=ko135(Citra);
MatKook=(mk000+mk045+mk090+mk135)/4;

I=[1:256];
SumX=sum(MatKook);  SumY=sum(MatKook');
MeanX=SumX*I';      MeanY=SumY*I';
StdX=sqrt((I-MeanX).^2*SumX');
StdY=sqrt((I-MeanY).^2*SumY');

CiriASM=sum(sum(MatKook.^2));
CiriCON=0;CiriCOR=0;CiriVAR=0;CiriIDM=0;CiriENT=0;
for i=1:256
    for j=1:256
        TempCON =  (i-j)*(i-j)*MatKook(i,j);
        TempCOR =  (i)*(j)*MatKook(i,j);
        TempVAR =  (i-MeanX)*(j-MeanY)*MatKook(i,j);
        TempIDM =  (MatKook(i,j))/(1+(i-j)*(i-j));
        TempENT = -(MatKook(i,j))*(log2(MatKook(i,j)+eps));
        
        CiriCON =  CiriCON + TempCON;
        CiriCOR =  CiriCOR + TempCOR;  
        CiriVAR =  CiriVAR + TempVAR;
        CiriIDM =  CiriIDM + TempIDM;
        CiriENT =  CiriENT + TempENT;
    end
end
CiriCOR=(CiriCOR-MeanX*MeanY)/(StdX*StdY);

fprintf('\n\tANGULAR SECOND MOMENTS     :%13.4f\n',CiriASM);
fprintf('\n\tCONTRAST                   :%13.4f\n',CiriCON);
fprintf('\n\tCORRELATION                :%13.4f\n',CiriCOR);
fprintf('\n\tVARIANCE                   :%13.4f\n',CiriVAR);
fprintf('\n\tINVERS DIFFERENCE MATRIX   :%13.4f\n',CiriIDM);
fprintf('\n\tENTROPY                    :%13.4f\n',CiriENT);

%ko000.m - MATRIKS KOOKURENSI ARAH 0 DERAJAT
function MatriksHasil=ko000(GambarAsli)
GambarAsli=double(GambarAsli);
Temp=zeros(256);
[tinggi,lebar]=size(GambarAsli);
for i=1:tinggi
    for j=1:lebar-1
           p=GambarAsli(i,j)+1;
           q=GambarAsli(i,j+1)+1;
           Temp(p,q) = Temp(p,q)+1 ;
           Temp(q,p) = Temp(q,p)+1 ;
    end
end
Jumlahpixel=sum(sum(Temp));
MatriksHasil=Temp/Jumlahpixel;

%ko045.m - MATRIKS KOOKURENSI ARAH 45 DERAJAT
function MatriksHasil=ko045(GambarAsli)
GambarAsli=double(GambarAsli);
Temp=zeros(256);
[tinggi,lebar]=size(GambarAsli);
for i=2:tinggi
    for j=1:lebar-1
            p=GambarAsli(i,j)+1;
            q=GambarAsli(i-1,j+1)+1;
            Temp(p,q) = Temp(p,q)+1;
            Temp(q,p) = Temp(q,p)+1;
    end
end
Jumlahpixel=sum(sum(Temp));
MatriksHasil=Temp/Jumlahpixel;

%ko090.m - MATRIKS KOOKURENSI ARAH 90 DERAJAT
function MatriksHasil=ko090(GambarAsli)
GambarAsli=double(GambarAsli);
Temp=zeros(256);
[tinggi,lebar]=size(GambarAsli);
for i=2:tinggi
    for j=1:lebar
        p=GambarAsli(i,j)+1;
        q=GambarAsli(i-1,j)+1;
        Temp(p,q) = Temp(p,q)+1 ;
        Temp(q,p) = Temp(q,p)+1 ;
    end
end
Jumlahpixel=sum(sum(Temp));
MatriksHasil=Temp/Jumlahpixel;

%ko135.m - MATRIKS KOOKURENSI ARAH 135 DERAJAT
function MatriksHasil=ko135(GambarAsli)
GambarAsli=double(GambarAsli);
Temp=zeros(256);
[tinggi,lebar]=size(GambarAsli);
for i=2:tinggi
    for j=2:lebar
        p=GambarAsli(i,j)+1;
        q=GambarAsli(i-1,j-1)+1;
        Temp(p,q) = Temp(p,q)+1 ;
        Temp(q,p) = Temp(q,p)+1 ;
    end
end
Jumlahpixel=sum(sum(Temp));
MatriksHasil=Temp/Jumlahpixel;

toc;

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