ANALISIS GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) DALAM MENGENALI CITRA EKSPRESI WAJAH ANALISIS GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) DALAM MENGENALI CITRA EKSPRESI WAJAH
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Abstract
Ekspresi wajah merupakan cara pengungkapan atau proses menyatakan maksud tertentu seperti sedih, bahagia, terkejut, takut, marah dan bad mood. Perubahan fitur wajah pada bibir, mata, pipi, membesarkan alis dan mulut terbuka dapat dijadikan variabel dalam menentukan maksud dari ekpresi wajah. Dataset yang digunakan dalam penelitian ini yaitu citra wajah dengan ekspresi : sedih, bahagia, terkejut, takut, marah, netral dan bad mood dengan ukuran 256x256. File citra yang digunakan untuk pelatihan maupun pengujian diambil dari situs http://www.kasrl.org/jaffeimages.zip dengan total keseluruhan sampling 213 citra ekspresi wajah. Klasifikasi ekspresi wajah menggunakan metode gray level co-occurrence matrix (GLCM). Hasil Klasifikasi pada ekspresi wajah netral GLCM mampu mengklasifikasi dengan rata-rata tingkat akurasi 33%, ekspresi marah 48%, ekspresi bahagia 73%, ekspresi bad mood 44%, ekspresi takut 15%, ekspresi sedih 54%, dan ekspresi terkejut 68%.
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