Feature Extraction of Tobacco Leaf Based on Discrete Cosine Transform (DCT)

JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Title Feature Extraction of Tobacco Leaf Based on Discrete Cosine Transform (DCT)
Ekstrasi Fitur Daun Tembakau Berbasis Discrete Cosine Transform (DCT)
 
Creator Nahari, Rosida Vivin
Editya, Arda Surya
Alfita, Riza
 
Description The success of the tobacco leaf classification process is very dependent on the extraction of tobacco leaf features. Several stages of digital image processing can improve the ability to identify the best quality tobacco automatically through extracting leaf texture features. This study aims to apply the leaf texture feature extraction system using the Discrete Cosine Transform method. Classification results measure the accuracy of the success of the system in extracting the best texture features. The classification of tobacco leaves requires extensive knowledge and complex terminology, even professional graders require significant time in this field for mastery of the subject. This is because tobacco leaves are usually considered to have characteristics that are useful for identification of tobacco quality where the extraction of appropriate features through leaf images can be considered a research problem that plays an important role for classification. The proposed research aims to find a suitable extraction model for obtaining color features through YCbCr color space conversion and tobacco leaf texture obtained from the transformation of the Discrete Cosine Transform frequency space. On classification stage in this research uses the maximum likelihood method. The trial results show an accuracy of success in the classification of tobacco leaves by 90% through the extraction of 12 features.
Keberhasilan proses klasifikasi daun tembakau sangat bergantung pada ekstrasi fitur daun tembakau.  Beberapa tahapan pengolahan citra digital dapat meningkatkan kemampuan dalam mengidentifikasi tembakau kualitas terbaik secara otomatis melalui ekstrasi fitur tekstur daun. Penelitian ini bertujuan untuk mengaplikasikan sistem ekstrasi fitur tekstur daun menggunakan metode Discrete Cosine Transform. Hasil Klasifikasi menjadi tolak ukur akurasi keberhasilan sistem dalam mengesktrasi fitur tekstur terbaik. Klasifikasi daun tembakau menuntut pengetahuan yang luas dan terminologi yang kompleks, bahkan grader profesional memerlukan waktu yang signifikan di bidang ini untuk penguasaan subjek. Hal ini disebabkan karena daun tembakau biasanya dianggap memiliki karakteristik yang berguna untuk identifikasi kualitas tembakau dimana ekstrasi fitur yang tepat melalui citra daun dapat dianggap sebagai masalah penelitian yang berperan penting untuk klasifikasi. Penelitian yang diusulkan bertujuan untuk menemukan model ekstrasi yang sesuai untuk mendapatkan fitur warna melalui konversi ruang warna YcbCr dan tekstur daun tembakau yang diperoleh dari transformasi ruang frekwensi Discrete Cosine Transform. Sedangkan untuk tahap klasifikasi menggunakan metode maximum likelihood. Hasil uji coba menunjukkan akurasi keberhasilan dalam pengklasifikasin daun tembakau sebesar 90 % melalui ekstrasi 12 fitur.
 
Publisher Politeknik Negeri Batam
 
Date 2020-02-04
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/1756
10.30871/jaic.v4i1.1756
 
Source Journal of Applied Informatics and Computing; Vol 4 No 1 (2020): Juli 2020; 8-12
2548-6861
10.30871/jaic.v4i1
 
Language eng
 
Relation https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/1756/1034
 
Rights Copyright (c) 2020 rosida vivin nahari
http://creativecommons.org/licenses/by-sa/4.0
 

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