DOI: https://doi.org/10.14710/jtsiskom.8.2.2020.94-99

Klasifikasi citra HSV aksara kuno pada prasasti tembaga Kintamani menggunakan GLRCM dan SVM

HSV image classification of ancient script on copper Kintamani inscriptions using GLRCM and SVM

STMIK STIKOM Indonesia, Indonesia

Received: 15 Apr 2019; Revised: 9 Dec 2019; Accepted: 18 Jan 2020; Available online: 5 Feb 2020; Published: 30 Apr 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
The problem of inscription physical damage as one of the historical heritages can be overcome using an image processing technique. The purpose of this study is to design a segmentation application for ancient scripts on inscriptions to recognize the character patterns on the inscriptions in digital form. The preprocessing was carried out to convert images from RGB to HSV. The application used the gray level run length matrix (GLRLM) to extract texture features and the support vector machine (SVM) method to classify the results. The inscription image segmentation was carried out through the pattern detection process using the sliding window method. The application obtained 88.32 % of accuracy, 0.87 of precision, and 0.94 of sensitivity.

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Keywords: segmentation; inscription; HSV image; GLRLM; SVM
Funding: STMIK STIKOM Indonesia

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Section: Original Research Articles
Language : ID
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