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All Journal Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknoinfo Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service
Agus Ambarwari
Politeknik Negeri Lampung
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Journal : Jurnal Teknoinfo

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Identification of Venation Type Based on Venation Density using Digital Image Processing Agus Ambarwari; Yeni Herdiyeni; Irman Hermadi
Jurnal Teknoinfo Vol 12, No 2 (2018): Juli
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v12i2.127

Abstract

Leaf venation is one biometric feature of leaves that have an important role in growth processes of the plant, and to determine the relationship of the plant physiology and the environment in which plants grow. At every different environment, plants have different types of leaf venation. It can be seen from the level of the leaf vein density. In this study, the feature of leaf vein density was used to identify the leaves based on venation type. The venation density features obtained from segmentation, vein detection, and density feature extraction of leaf venation. Identification of the venation type was made using the artificial neural network (ANN). The results of this study indicate that the proposed method can classify the leaf correctly image based on the venation type. On the dataset with 324 samples, the accuracy of 82.71% was obtained. This shows that the leaf vein density features allow use as a plant identifier.Keywords: leaf vein density, vein detection, density feature extraction, artificial neural network
Co-Authors Anung Wahyudi Dewi Kania Widyawati Emir Mauludi Husni Imam Ahmad Iqbal Yasin Irman Hermadi Muhammad Adam Putra Darma Muharman Lubis Neneng Neneng Qadhli Jafar Adrian Rohmat Indra Borman Yusmaida Yusmaida Yusra Fernando