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Image Classification with Shell Texture Feature Extraction Using Local Binary Pattern (LBP) Method

Applied Technology and Computing Science Journal

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Field Value
 
Title Image Classification with Shell Texture Feature Extraction Using Local Binary Pattern (LBP) Method
 
Creator Devi, Putri Aisyiyah Rakhma
Budiarti, Rizqi Putri Nourma
 
Subject texture feature extraction
LBP
classification
shell image
 
Description Classification procedure that is usually done manually by way of separation based on the texture of the shell shell. Classification is done by looking at objects based on inherent characteristics usually referred to as features / characteristics. Classification by hand can cause accuracy problems. In the image of the shells, texture characteristics are needed to distinguish one type of shell from another. The purpose of this study is to develop a texture feature extraction system for the classification of shell images. The input image is carried out preprocessing and segmenting to separate objects from the background and the image of the separated object is transformed into a grayscale image for the feature extraction process using the Local Binary Pattern method. Based on trials that have been done, the accuracy is quite good, the highest accuracy value occurs in shellfish blood cockles with RBF kernels. While the lowest accuracy is on testing the feather shell image where the accuracy value is 86.6% this result can show that the LBP method with SVM classification is quite reliable in calculating the accuracy for the classification process of shellfish types.
 
Publisher Unusa Press
 
Date 2020-09-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://journal2.unusa.ac.id/index.php/ATCSJ/article/view/1745
10.33086/atcsj.v3i1.1745
 
Source Applied Technology and Computing Science Journal; Vol. 3 No. 1 (2020): June; 48-57
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER; Vol 3 No 1 (2020): June; 48-57
2621-4474
2621-4458
10.33086/atcsj.v3i1
 
Language eng
 
Relation https://journal2.unusa.ac.id/index.php/ATCSJ/article/view/1745/1183
 
Rights Copyright (c) 2020 Putri Aisyiyah Rakhma Devi, Rizqi Putri Nourma Budiarti
https://creativecommons.org/licenses/by-sa/4.0