IJTB | INTERNATIONAL JOURNAL OF TECHNOLOGY AND BUSINESS
Vol 2, No 2 (2016)

Identifikasi Citra Daun Menggunakan Morfologi, Local Binary Patterns dan Convex Hulls

Prasvita, Desta Sandya (Unknown)

Article Info

Publish Date
22 Aug 2016

Abstract

This research proposes a leaf identification system with features fusion of leafmorphology, convex hulls (shape features) and 𝐿𝐵𝑃𝑃,𝑅 𝑟𝑖𝑢2 (texture features). Probabilistic Neural Network (PNN) is used as classifier. The experimental results of leaf identification system, average accuracy of combining all the features is 87.5%. Accuracy by combining three features higher than using morphological features (58.125%) or texture features (68.125%). In this research showed that the texture features more influence than morphological features for recognition of plants.

Copyrights © 2016




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
IJTB | INTERNATIONAL JOURNAL OF TECHNOLOGY AND BUSINESS
Website

Abbrev

i-statement

Publisher

Sekolah Tinggi Ilmu Manajemen dan Ilmu Komputer ESQ

Subject

Computer Science & IT Other

Description

I-STATEMENT (Information Systems and Technology Management) is published twice annually to demonstrate the latest scientific research that tests, extends and builds the theory of information systems and technology management and contributes directly to the practical world of information systems and ...