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Journal : Jurnal ULTIMA Computing

Klasifikasi Citra Daun dengan Metode Gabor Co-Occurence Mutmainnah Muchtar; Laili Cahyani
Ultima Computing : Jurnal Sistem Komputer Vol 7 No 2 (2015): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (888.943 KB) | DOI: 10.31937/sk.v7i2.231

Abstract

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