Klasifikasi Citra Daun dengan Metode Gabor Co-Occurence

Abstract: Plant takes a crucial part in mankindexistences. The development of digital imageprocessing technique made the plant classification task become a lot of easier. Leaf is a part of plantthat can be used for plant classifcation wheretexture of the leaf is a common feature that beenused for classifcation process. Texture offers a unique feature and able to work even whenthe leaf is damaged or overly big in size whichsometimes made the acquisition process become more difcult. This study offers a combination ofGabor flter methods and co-occurrence matricesto produce the most representative features for leaf classifcation. Classifcation using SVM with 5-fold cross validation system shows that the proposed Gabor Co-Occurence methods was able to reach average accuracy up to 89.83%.
Terms: Leaf, Gabor Co-occurence, Support Vector Machine, Texture
Penulis: Mutmainnah Muchtar dan Laili Cahyani
Kode Jurnal: jptkomputerdd150423

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