Grape leaf image disease classification using CNN-VGG16 model
Open Access
- 5 July 2021
- journal article
- Published by Institute of Research and Community Services Diponegoro University (LPPM UNDIP) in Jurnal Teknologi dan Sistem Komputer
- Vol. 9 (4), 218-223
- https://doi.org/10.14710/jtsiskom.2021.14013
Abstract
This study aims to classify the disease image on grape leaves using image processing. The segmentation uses the k-means clustering algorithm, the feature extraction process uses the VGG16 transfer learning technique, and the classification uses CNN. The dataset is from Kaggle of 4000 grape leaf images for four classes: leaves with black measles, leaf spot, healthy leaf, and blight. Google images of 100 pieces were also used as test data outside the dataset. The accuracy of the CNN model training is 99.50 %. The classification yields an accuracy of 97.25 % using the test data, while using test image data outside the dataset obtains an accuracy of 95 %. The designed image processing method can be applied to identify and classify disease images on grape leaves.Keywords
Funding Information
- Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
This publication has 12 references indexed in Scilit:
- Fish Species Recognition Using VGG16 Deep Convolutional Neural NetworkJournal of Computing Science and Engineering, 2019
- Identification of grape diseases using image analysis and BP neural networksMultimedia Tools and Applications, 2019
- Analisis Hama pada Tanaman Anggur dengan Pendekatan Metode CF (Certainty Factor) Berbasis Mobile AndroidSMATIKA JURNAL, 2018
- Malicious Software Classification Using VGG16 Deep Neural Network’s Bottleneck FeaturesPublished by Springer Science and Business Media LLC ,2018
- Digital TV and Wireless Multimedia CommunicationPublished by Springer Science and Business Media LLC ,2018
- Grape leaf disease detection and classification using multi-class support vector machinePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- PENERAPAN DATAMINING PADA POPULASI DAGING AYAM RAS PEDAGING DI INDONESIA BERDASARKAN PROVINSI MENGGUNAKAN K-MEANS CLUSTERINGInfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan), 2017
- An individual grape leaf disease identification using leaf skeletons and KNN classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- SVM classifier based grape leaf disease detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Klasifikasi Citra Menggunakan Convolutional Neural Network (CNN) pada Caltech 101Jurnal Teknik ITS, 2016