Tahun 2011 Nama Peneliti/Mahasiswa ADITYA DWI GUSADHA ...

haremboingAI and Robotics

Oct 20, 2013 (4 years and 20 days ago)

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http://alihjenis.cs.ipb.ac.id

Tahun

2011


Nama Peneliti/Mahasiswa

ADITYA DWI GUSADHA (G64076010)


Judul

Identifikasi Jenis Aglonema Menggunakan Metode Local Binnary Pattern Descriptor dan Self
Organizing Maps


Judul (
English
)

Aglaonema Type Identification System Using Probabilistic Neu
ral Network


Pembimbing

Yeni Herdiyeni


Abstrak/Ringkasan

ABSTRAK ADITYA DWI GUSADHA. Aglaonema Type Identification System Using Probabilistic
Neural Network. Supervised by AZIZ KUSTIYO. Aglaonema is an ornamental plant that is quite
popular in Indonesia.
It is estimated that there are nearly 8000 species Aglaonema in the world both
native and hybrid. The many types of Aglaonema in the world causes difficult in identifying some
types of Aglaonema. This research attempts to identify the type of Aglaonema bas
ed on the image
using Probabilistic Neural Network (PNN). The data used in this study have 900 images of leaves,
which consists of 30 types of Aglaonema. Each image of Aglaonema that will be identified by the
system will first be subjected to two stages, t
exture feature extraction and colour feature extraction.
The texture feature extraction used Local Binary Pattern Variance (LBPV) and Cooccurrence
Matrix while the colour feature extraction used Histogram162 (HSV162). We perform two type of
experiment, one

where we uses each feature seperately and another where the two features are
combine. For classifier we used Probabilistic Neural Network (PNN). The results indicates that the
combination of Cooccurrence Matrix with HSV162 yield a better accuracy compact
two when the
feature are used seperately. On the other hand, the combination of Local Binnary Pattern Variance
(LBPV) and HSV162 does not yield an increase in accuracy, however the accuracy on this case is
better than the accuracy of the combination betwee
n Cooccurrence Matrix and HSV162. The
highest accuracy is obtained in the case of the Local Binnary Pattern Variance (LBPV) and HSV162
with the value of 55.56%.



Keywords
: Aglaonema, Probabilistic Neural Network, Co
-
occurrence Matrix, Local Binary Pattern

Variance, Histogram
-
162.