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Desi Andreswari
Department of Informatics, Universitas Bengkulu
Computer Science & IT Electrical & Electronics Engineering

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Identifikasi Jenis Bambu Berdasarkan Tekstur Daun dengan Metode Gray Level Co-Occurrence Matrix dan Gray Level Run Length Matrix Endina Putri Purwandari; Rachmi Ulizah Hasibuan; Desi Andreswari
Jurnal Teknologi dan Sistem Komputer Volume 6, Issue 4, Year 2018 (October 2018)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.891 KB) | DOI: 10.14710/jtsiskom.6.4.2018.146-151

Abstract

Bamboo species can be identified from the bamboo leaf images. This study conducted the identification of bamboo species based on leaf texture using Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM) for texture feature extraction, and Euclidean distance for measure the image distance. This study used the images of bamboo species in Bengkulu province, that are bambusa Vulgaris Var Vulgaris, bambusa Multiplex, bambusa Vulgaris Var Striata, Gigantochloa Robusta, Gigantochloa Schortrchinii, Gigantochloa Serik, Schizostachyum Brachycladum, and Dendrocalamus Asper. The bamboo application was built using Matlab. The accuracy of the application was 100% for bamboo leaf test images captured using a smartphone camera and 81.25% for test images downloaded from the Internet.
Co-Authors Endina Putri Purwandari Rachmi Ulizah Hasibuan