Jurnal Teknoinfo
Vol 12, No 2 (2018): Juli

Identification of Venation Type Based on Venation Density using Digital Image Processing

Agus Ambarwari (Universitas Teknokrat Indonesia)
Yeni Herdiyeni (Institut Pertanian Bogor)
Irman Hermadi (Institut Pertanian Bogor)



Article Info

Publish Date
15 Jul 2018

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

Copyrights © 2018






Journal Info

Abbrev

teknoinfo

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknoinfo is a peer-reviewed scientific Open Access journal that published by Universitas Teknokrat Indonesia. This Journal is built with the aim to expand and create innovation concepts, theories, paradigms, perspectives and methodologies in the sciences of Informatics Engineering. The ...