Please use this identifier to cite or link to this item:
http://repository.ipb.ac.id/handle/123456789/65310
Title: | Identifikasi Citra Hama Tomat Menggunakan Gray Level Co-occurrence Matrix dan Klasifikasi Probabilistic Neural Network |
Authors: | Haryanto, Toto Maryana, Nina Amalia, Rizkia Hanna |
Keywords: | Bogor Agricultural University (IPB) tomato pest Probabilistic Neural Network object identification Level Co-occurrence Matrix |
Issue Date: | 2013 |
Abstract: | Pests cause a major failures in harvesting tomato plants. Identification of tomato pests can be done in various ways. Nowadays, objects can be performed by processing digital images. In this research, Gray Level Co-occurrence Matrix (GLCM) is used to identify three classes of plant pests of tomato, namely Helicoverpa armigera, Spodoptera litura and Chrysodeixis chalcites. For identification, only three types of pests in adults phase was used. Identification is conducted using the five elements of grayscale image: energy, homogeneity, contrast, correlation and entropy. The identification result using Probabilistic Neural Network (PNN) produces average accuracy of 78.89%. |
URI: | http://repository.ipb.ac.id/handle/123456789/65310 |
Appears in Collections: | UT - Computer Science |
Files in This Item:
File | Size | Format | |
---|---|---|---|
G13rha1.pdf Restricted Access | 2.07 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.