Performance Improvement of Leaf Identification System Using Principal Component Analysis
This paper reports the results of experiments in improving performance of leaf identification system using Principal Component Analysis (PCA). The system involved combination of features derived from shape, vein, color, and texture of leaf. PCA was incorporated to the identification system to conver...
Saved in:
Main Authors: | Kadir, Abdul, Nugroho, Lukito Edi, Susanto, Adhi, Santosa, Paulus Insap |
---|---|
Format: | Article PeerReviewed |
Language: | English |
Published: |
2012
|
Subjects: | |
Online Access: | https://repository.ugm.ac.id/36084/1/Performance_Improvement_of_Leaf_Identification_System_Using_Principal_Component_Analysis.pdf https://repository.ugm.ac.id/36084/ http://www.sersc.org/journals/IJAST/vol44.php |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universitas Gadjah Mada |
Language: | English |
Similar Items
-
EXPERIMENTS OF ZERNIKE MOMENTS FOR LEAF IDENTIFICATION
by: Kadir, Abdul, et al.
Published: (2012) -
Principal Component Analysis Combined with Second Order Statistical Feature Method for Malaria Parasites Classification
by: Wahab, Iis Hamsir Ayub, et al.
Published: (2014) -
Experiments of Distance Measurements in a Foliage Plant Retrieval System
by: Kadir, Abdul, et al.
Published: (2012) -
Tensor principal component analysis
by: ZHOU, Pan, et al.
Published: (2022) -
Unsupervised feature selection based on principal components analysis
by: Fang, Ji
Published: (2008)