Pixel 4,2 = 96B491
= 1001 0110 1011 0100 1001 0001 Pixel 4,3
= 96A4FF = 1001 0110 1010 0100 1111 1111
Pixel 4,4 = C3B425
= 1100 0011 1011 0100 0010 0101 3.1.6.2 Segmentasi
Tahap pertama dalam sistem pengenalan iris mata adalah memisahkan daerah iris mata pada suatu citra mata. Hal ini disebabkan daerah iris mata dipengaruhi bulu mata dan kelopak
mata, inilah penyebab terjadinya noise dalam mengenali pemilik citra iris. Adapun dalam penelitian ini segmentasi dilakukan dengan proses penghalusan smoothing yaitu
menggunakan Gaussian Filter, Grayscale, Threshold Binerisasi, dan terakhir dengan deteksi tepi.
3.1.6.2.1 Gaussian Filter
Gaussian Filter secara meluas telah digunakan dalam bidang analisis citra terutama untuk proses penghalusan smoothing, pengaburan bluring, menghilangkan detail, dan
menghilangkan derau noise dan merupakan salah satu proses memperhalus gambar yang dinilai sudah cukup optimal. Proses penghalusan citra dilakukan dengan melakukan
konvolusi citra dengan filter kernel Gaussian seperti pada Tabel 3.4 Tabel 3.4 Matriks Kernel Gaussian 2 D 5 x 5
0.0030 0.0133
0.0219 0.0133
0.0030 0.0133
0.0596 0.0983
0.0596 0.0133
0.0219 0.0983
0.1621 0.0983
0.0219 0.0133
0.0596 0.0983
0.0596 0.0133
0.0030 0.0133
0.0219 0.0133
0.0030 Matriks citra awal dalam heksadesimal dapat dilihat pada Tabel 3.5
Tabel 3.5 Matriks Citra Iris Heksadesimal 90B4F1
90B4F1 93B4F1
10B491 90E1F1
96B491 90B411
98B491 9034F1
15D411 F3B415
F4B4D1 8024F0
8946837 22C480
90B4F1 90F4C1
90B7F9 90B4F1
740491 F3B491
9CB6C1 96B491
96A4FF C3B425
Agar dapat dikonvolusi dengan matriks kernel maka nilai heksadesimal diubah ke dalam bentuk desimal seperti terlihat pada Tabel 3.6.
Tabel 3.6 Nilai Heksadesimal Diubah Dalam Desimal 9483505
9483505 9680113
1094801 9495025
9876625 9483281 10007697 9450737
1430545 15971349 16037073 8398064
9876625 2278528
9483505 9499841
9484281 9483505
7603345 15971473 10270401 9876625
9872639 12825637 Hasil konvolusi yaitu perkalian Matriks kernel dengan nilai piksel:
0.0030 9483505 =
28450,515 0.0133 9483505
= 126130,6165
0.0219 9680113 =
211994,4747 0.01331094801
= 14560,8533
0.00309495025 =
28485,075 0.0133 9876625
= 129383,7875
0.0596 9483281 =
554771,9385 0.0983 10007697
= 965742,7605
0.0596 9450737 =
552868,1145 0.0133 1430545
= 18740,1395
0.021915971349 =
349772,5431 0.0983 9483281
= 932206,5223
0.1621 8398064 =
1361326,1744 0.0983 9876625
= 970872,2375
0.0219 2278528 =
49899,7632 0.0133 9876625
= 131359,1125
0.0596 9499841 =
566190,5236 0.0983 9484281
= 932304,8223
0.0596 9483505 =
565216,898 0.0133 7603345
= 101124,4885
0.0030 15971473 =
47914,419 0.013310270401
= 136596,3333
0.0219 9876625 =
216298,0875 0.0133 9872639
= 131306,0987
0.0030 12825637 =
38476,911 Berikut adalah hasil dari konvolusi Matriks kernel dengan nilai matriks citra pada tabel 3.7
dari iris mata.
Tabel 3.7 Hasil Dari Konvolusi Citra Dengan Matriks Kernel
28450,515 129383,7875 349772,5431 131359,1125
47914,419 126130,6165 554771,9385 932206,5223 566190,5236
136596,3333 211994,4747 965742,7605 1361326,1744 932304,8223
216298,0875 14560,8533
552868,1145 970872,2375 565216,898
131306,0987 28485,075
18740,1395 49899,7632
101124,4885 38476,911
Dari perhitungan konvolusi lanjut ke perhitungan RGB, Selanjunya dilakukan perhitungan nilai RGB dengan rumus:
Nilai R = c and 255...............................................................................................................3.1 Nilai G = c and 65,280256
................................................................................................ 3.2
Nilai B = c and 16,711,680256256...............................................................................3.3 Dari nilai bitmap di atas dapat dihitung nilai komponen RGB citra dengan menggunakan
persamaan 3.1, 3.2 dan 3.3. Pixel 0,0:
Nilai R = c and 255 28450 and 255
= 34
Nilai G = c and 65.280256 28450 and 65.280 256 = 2560256 = 111
Nilai B = c and 16.711.680256256 28450 and 16.711.680 256256 = 0
Pixel 0,1: Nilai R = c and 255
126130 and 255 = 178
Nilai G = c and 65.280256 126130 and 65.280 256 = 236
Nilai B = c and 16.711.680256256 126130 and 16.711.680256256 = 256
Pixel 0,2: Nilai R = c and 255
211994 and 255 = 234 Nilai G = c and 65.280256
211994 and 65.280256 = 60 Nilai B = c and 16.711.680256256
211994 and 16.711.680256256 = 3 Pixel 0,3:
Nilai R = c and 255
14560 and 255 = 5 Nilai G = c and 65.280256
14560 and 65.280256 = 56 Nilai B = c and 16.711.680256256
14560 and 16.711.680256256 = 0
Pixel 0,4: Nilai R = c and 255
28485 and 255 = 193 Nilai G = c and 65.280256
28485 and 65.280256 = 10 Nilai B = c and 16.711.680256256
28485 and 16.711.680256256 = 0 Pixel 1,0:
Nilai R = c and 255
129383 and 255 = 103 Nilai G = c and 65.280256
129383 and 65.280256 = 249 Nilai B = c and 16.711.680256256
12938 and 16.711.680256256 = 0 Pixel 1,1:
Nilai R = c and 255
554771 and 255 = 19 Nilai G = c and 65.280256
554771 and 65.280256 = 119 Nilai B = c and 16.711.680256256
554771 and 16.711.680256256 = 8 Pixel 1,2:
Nilai R = c and 255
965742 and 255 = 110 Nilai G = c and 65.280256
965742 and 65.280256 = 188 Nilai B = c and 16.711.680256256
965742 and 16.711.680256256 = 14 Pixel 1,3:
Nilai R = c and 255
552868 and 255 = 164 Nilai G = c and 65.280256
552868 and 65.280256 = 111 Nilai B = c and 16.711.680256256
552868 and 16.711.680256256 = 8 Pixel 1,4:
Nilai R = c and 255
18740 and 255 = 52 Nilai G = c and 65.280256
18740 and 65.280256 = 73 Nilai B = c and 16.711.680256256
18740 and 16.711.680256256 = 0 Pixel 2,0:
Nilai R = c and 255
349772 and 255 = 76 Nilai G = c and 65.280256
349772 and 65.280256 = 86 Nilai B = c and 16.711.680256256
349772 and 16.711.680256256 = 5 Pixel 2,1:
Nilai R = c and 255
932206 and 255 = 110 Nilai G = c and 65.280256
932206 and 65.280256 = 57 Nilai B = c and 16.711.680256256
932206 and 16.711.680256256 = 14 Pixel 2,2:
Nilai R = c and 255
1361326 and 255 = 174 Nilai G = c and 65.280256
1361326 and 65.280256 = 197 Nilai B = c and 16.711.680256256
1361326 and 16.711.680256256 = 20 Pixel 2,3:
Nilai R = c and 255
970872 and 255 = 120 Nilai G = c and 65.280256
970872 and 65.280256 = 208 Nilai B = c and 16.711.680256256
970872 and 16.711.680256256 = 14 Pixel 2,4:
Nilai R = c and 255
49899 and 255 = 235 Nilai G = c and 65.280256
49899 and 65.280256 = 194 Nilai B = c and 16.711.680256256
49899 and 16.711.680256256 = 0 Pixel 3,0:
Nilai R = c and 255
131359 and 255 = 31 Nilai G = c and 65.280256
131359 and 65.280256 = 1 Nilai B = c and 16.711.680256256
131359 and 16.711.680256256 = 2 Pixel 3,1:
Nilai R = c and 255
566190 and 255 = 174 Nilai G = c and 65.280256
566190 and 65.280256 = 163 Nilai B = c and 16.711.680256256
566190 and 16.711.680256256 = 8 Pixel 3,2:
Nilai R = c and 255
932304 and 255 = 33 Nilai G = c and 65.280256
932304 and 65.280256 = 247 Nilai B = c and 16.711.680256256
932304 and 16.711.680256256 = 13 Pixel 3,3:
Nilai R = c and 255
565216 and 255 = 33 Nilai G = c and 65.280256
565216 and 65.280256 = 119 Nilai B = c and 16.711.680256256
565216 and 16.711.680256256 = 8 Pixel 3,4:
Nilai R = c and 255
101124 and 255 = 19 Nilai G = c and 65.280256
101124 and 65.280256 = 133 Nilai B = c and 16.711.680256256
101124 and 16.711.680256256 = 1 Pixel 4,0:
Nilai R = c and 255
47914 and 255 = 42 Nilai G = c and 65.280256
47914 and 65.280256 = 187 Nilai B = c and 16.711.680256256
47914 and 16.711.680256256 = 0 Pixel 4,1:
Nilai R = c and 255
136596 and 255 = 148 Nilai G = c and 65.280256
136596 and 65.280256 = 21 Nilai B = c and 16.711.680256256
136596 and 16.711.680256256 = 2 Pixel 4,2:
Nilai R = c and 255
216298 and 255 = 234 Nilai G = c and 65.280256
216298 and 65.280256 = 76 Nilai B = c and 16.711.680256256
216298 and 16.711.680256256 = 1 Pixel 4,3:
Nilai R = c and 255
131306 and 255 = 234 Nilai G = c and 65.280256
131306 and 65.280256 = 0 Nilai B = c and 16.711.680256256
131306 and 16.711.680256256 = 2 Pixel 4,4:
Nilai R = c and 255
38476 and 255 = 76 Nilai G = c and 65.280256
38476 and 65.280256 = 150 Nilai B = c and 16.711.680256256
38476 and 16.711.680256256 = 0 Langkah di atas dilakukan sampai pixel 4,4 dan nilai RBG dimasukkan ke dalam matriks
RGB citra seperti pada Tabel 3.8. Tabel 3.8 Hasil Matriks Citra Iris RGB
x,y 1
