Pemanfaatan Ciri Gray Level Co-occurrence Matrix (GLCM) Untuk Deteksi Melasma Pada Citra Wajah - Winda Ika Praseptiyana; Agus Wahyu Widodo; Muh Arif Rahman (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Skin is the outermost human organ with the highest sensitivity from external environment, it can cause skin diseases. Skin disease in tropical countries like Indonesia is melasma. Melasma is caused by excessive use of cosmetics and contact with ultraviolet light. If allowed to damage skin cells, damage DNA and risk of skin cancer. Examination on site by a dermatologist relies on visual examination and history taking, which does not rule out the possibility on inaccurate analysis and diagnosis. Therefore, patients choose to do selfcare. However, selfcare can cause melasma to get worse if it is misidentified. Therefore, a detection system is needed to help identify melasma automatically. Using 20 face images data divided into 16 training images and 4 testing images. Face image come in processed cropping images in non-overlapping sliding window to get the window images, then converted to grayscale images. Using the Gray Level Co-occurrence Matrix (GLCM) method as texture extraction with combination angle is 0 °, 45 °, 90 °, 135 ° and neighboring distance value d = 1,2,3. Use of GLCM features are contrast, homogeneity, energy and entropy. For classification method using K-Nearest Neighbor (KNN) with value k=5. This research success in testing of window images, the best percentage was 98% with window size of 200x200 pixels, angular direction with 3 combination is 0°+45°+90° and distance of neighborhood is d = 2.