Klasifikasi Citra Daun dengan Metode Gabor Co-Occurence

  • Mutmainnah Muchtar Institut Teknologi Sepuluh Nopember
  • Laili Cahyani Institut Teknologi Sepuluh Nopember


Plant takes a crucial part in mankind existences. The development of digital image processing technique made the plant classification task become a lot of easier. Leaf is a part of plant that can be used for plant classification where texture of the leaf is a common feature that been used for classification process. Texture offers a unique feature and able to work even when the leaf is damaged or overly big in size which sometimes made the acquisition process become more difficult. This study offers a combination of Gabor filter methods and co-occurrence matrices to produce the most representative features for leaf classification. Classification 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


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How to Cite
Muchtar, M., & Cahyani, L. (2016). Klasifikasi Citra Daun dengan Metode Gabor Co-Occurence. Ultima Computing : Jurnal Sistem Komputer, 7(2), 39-47. https://doi.org/https://doi.org/10.31937/sk.v7i2.231