first commit
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close all;
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dataDirBuahNaga = fullfile('D:\PROPOSAL\Data skripsi\Buah naga merah\');
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filenamesBuahNaga = dir(fullfile(dataDirBuahNaga, '*.JPG'));
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total_images = numel(filenamesBuahNaga);
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% for n = 1:total_images
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for n = 1:1000
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full_nameBuahnaga = fullfile(dataDirBuahNaga, filenamesBuahNaga(n).name);
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gambar1 = imread(full_nameBuahnaga);
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%mengubah ukuran jadi 400x400
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gambar = imresize(gambar1,[400,400]);
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% figure, imshow(gambar);
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gray_image = im2gray(gambar);
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% %figure, imshow(gray_image);
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file_ALL = strcat('D:\PROPOSAL\Data Preprocessing\Data Grayscale Kecil\', filenamesBuahNaga(n).name);
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imwrite(gray_image,file_ALL);
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I = gray_image;
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[tinggi, lebar] = size (I);
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% Bentuk GLCM
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GLCM0 = zeros(256, 256);
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total_piksel0 = 0;
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GLCM45 = zeros(256, 256);
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total_piksel45 = 0;
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GLCM90 = zeros(256, 256);
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total_piksel90 = 0;
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GLCM135 = zeros(256, 256);
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total_piksel135 = 0;
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for y = 2: tinggi-1
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for x = 2: lebar-1
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% untuk sudut 0
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a = I(y,x);
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b = I(y,x+1);
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GLCM0(a+1, b+1) = GLCM0(a+1, b+1) + 1;
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total_piksel0 = total_piksel0 + 1;
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% untuk sudut 45
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a = I(y,x);
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b = I(y-1,x+1);
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GLCM45(a+1, b+1) = GLCM45(a+1, b+1) + 1;
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total_piksel45 = total_piksel45 + 1;
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% untuk sudut 90
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a = I(y,x);
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b = I(y-1,x);
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GLCM90(a+1, b+1) = GLCM90(a+1, b+1) + 1;
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total_piksel90 = total_piksel90 + 1;
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% untuk sudut 135
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a = I(y,x);
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b = I(y-1,x-1);
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GLCM135(a+1, b+1) = GLCM135(a+1, b+1) + 1;
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total_piksel135 = total_piksel135 + 1;
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end
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end
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GLCM0 = GLCM0 / total_piksel0;
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GLCM45 = GLCM45 / total_piksel45;
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GLCM90 = GLCM90 / total_piksel90;
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GLCM135 = GLCM135 / total_piksel135;
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%Hitung ASM
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asm0 = 0.0;
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asm45 = 0.0;
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asm90 = 0.0;
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asm135 = 0.0;
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for a = 0 : 255
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for b = 0 : 255
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asm0 = asm0 + (GLCM0(a+1,b+1) * GLCM0(a+1,b+1));
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asm45 = asm45 + (GLCM45(a+1,b+1) * GLCM45(a+1,b+1));
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asm90 = asm90 + (GLCM90(a+1,b+1) * GLCM90(a+1,b+1));
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asm135 = asm135 + (GLCM135(a+1,b+1) * GLCM135(a+1,b+1));
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end
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end
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%Hitung IDM
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idm0 = 0.0;
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idm45 = 0.0;
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idm90 = 0.0;
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idm135 = 0.0;
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for a = 0 : 255
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for b = 0 : 255
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idm0 = idm0 + (GLCM0(a+1,b+1) / (1+(a-b)*(a-b)));
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idm45 = idm45 + (GLCM45(a+1,b+1) / (1+(a-b)*(a-b)));
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idm90 = idm90 + (GLCM90(a+1,b+1) / (1+(a-b)*(a-b)));
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idm135 = idm135 + (GLCM135(a+1,b+1) / (1+(a-b)*(a-b)));
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end
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end
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%Hitung Kontras
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kontras0 = 0.0;
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kontras45 = 0.0;
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kontras90 = 0.0;
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kontras135 = 0.0;
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for a = 0 : 255
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for b = 0 : 255
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kontras0 = kontras0 + (a-b)*(a-b)* GLCM0(a+1,b+1);
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kontras45 = kontras45 + (a-b)*(a-b)* GLCM45(a+1,b+1);
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kontras90 = kontras90 + (a-b)*(a-b)* GLCM90(a+1,b+1);
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kontras135 = kontras135 + (a-b)*(a-b)* GLCM135(a+1,b+1);
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end
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end
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%Hitung Kovarians
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korelasi0 = 0.0;
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px0 = 0;
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py0 = 0;
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reratax0 = 0.0;
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reratay0 = 0.0;
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stdevx0 = 0.0;
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stdevy0 = 0.0;
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korelasi45 = 0.0;
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px45 = 0;
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py45 = 0;
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reratax45 = 0.0;
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reratay45 = 0.0;
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stdevx45 = 0.0;
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stdevy45 = 0.0;
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korelasi90 = 0.0;
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px90 = 0;
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py90 = 0;
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reratax90 = 0.0;
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reratay90 = 0.0;
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stdevx90 = 0.0;
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stdevy90 = 0.0;
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korelasi135 = 0.0;
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px135 = 0;
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py135 = 0;
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reratax135 = 0.0;
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reratay135 = 0.0;
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stdevx135 = 0.0;
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stdevy135 = 0.0;
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for a = 0 : 255
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for b = 0 : 255
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px0 = px0 + a * GLCM0 (a+1, b+1);
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py0 = py0 + b * GLCM0 (a+1, b+1);
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px45 = px45 + a * GLCM45 (a+1, b+1);
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py45 = py45 + b* GLCM45 (a+1, b+1);
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px90 = px90 + a * GLCM90 (a+1, b+1);
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py90 = py90 + b * GLCM90 (a+1, b+1);
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px135 = px135 + a * GLCM135 (a+1, b+1);
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py135 = py135 + b * GLCM135 (a+1, b+1);
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end
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end
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%Hitung deviasi standar
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for a = 0 : 255
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for b = 0 : 255
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stdevx0 = stdevx0 + (a-px0) * (a-px0) * GLCM0(a+1, b+1);
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stdevy0 = stdevy0 + (b-py0) * (b-py0) * GLCM0(a+1, b+1);
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stdevx45 = stdevx45 + (a-px45) * (a-px45) * GLCM45(a+1, b+1);
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stdevy45 = stdevy45 + (b-py45) * (b-py45) * GLCM45(a+1, b+1);
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stdevx90 = stdevx90 + (a-px90) * (a-px90) * GLCM90(a+1, b+1);
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stdevy90 = stdevy90 + (b-py90) * (b-py90) * GLCM90(a+1, b+1);
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stdevx135 = stdevx135 + (a-px135) * (a-px135) * GLCM135(a+1, b+1);
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stdevy135 = stdevy135 + (b-py135) * (b-py135) * GLCM135(a+1, b+1);
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end
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end
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%Hitung Korelasi
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for a = 0 : 255
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for b = 0 : 255
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korelasi0 = korelasi0 + ((a-px0)*(b-py0) * GLCM0(a+1, b+1)/(stdevx0*stdevy0));
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korelasi45 = korelasi45 + ((a-px45)*(b-py45) * GLCM45(a+1, b+1)/(stdevx45*stdevy45));
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korelasi90 = korelasi90 + ((a-px90)*(b-py90) * GLCM90(a+1, b+1)/(stdevx90*stdevy90));
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korelasi135 = korelasi135 + ((a-px135)*(b-py135) * GLCM135(a+1, b+1)/(stdevx135*stdevy135));
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end
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end
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%Hitung Fitur
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G0asm = asm0;
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G0idm = idm0;
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G0kontras = kontras0;
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G0korelasi = korelasi0;
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G45asm = asm45;
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G45idm = idm45;
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G45kontras = kontras45;
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G45korelasi = korelasi45;
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G90asm = asm90;
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G90idm = idm90;
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G90kontras = kontras90;
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G90korelasi = korelasi90;
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G135asm = asm135;
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G135idm = idm135;
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G135kontras = kontras135;
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G135korelasi = korelasi135;
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fitur = [G0asm ;G0idm ;G0kontras ;G0korelasi
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;G45asm ;G45idm ;G45kontras ;G45korelasi
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;G90asm ;G90idm ;G90kontras ;G90korelasi
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;G135asm ;G135idm ;G135kontras ;G135korelasi];
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fitur_post(n,:)=fitur(1:16,:);
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xlswrite('data_latih.xlsx',fitur_post);
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% klasifikasi naive bayes
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load 'D:\PROPOSAL\Data skripsi\Buah naga merah\class.mat'
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X = fitur_post;
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Y = class;
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rng('default')
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cv = cvpartition(Y,'HoldOut',0.20);
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trainInds = training(cv);
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testInds = test(cv);
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XTrain = X(trainInds,:);
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YTrain = Y(trainInds);
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XTest = X(testInds,:);
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YTest = Y(testInds);
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Mdl = fitcnb(XTrain,YTrain,'ClassNames',{'buah naga bagus','buah naga jelek','buah naga cacar'})
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idx = randsample(sum(testInds),30);
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label = predict(Mdl,XTest);
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table(YTest(idx),label(idx),'VariableNames',...
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{'TrueLabel','PredictedLabel'})
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cm = confusionchart(YTest,label);
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cm.ColumnSummary = 'column-normalized';
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cm.RowSummary = 'row-normalized';
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cm.Title = 'Buah Naga Confusion Matrix';
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end
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